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Raquel Urtasun

Raquel Urtasun Waabi

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affiliation: University of Toronto, Canada
affiliation: Waabi
affiliation (former): Swiss Federal Institute of Technology in Lausanne, Switzerland

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Journal Articles

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2022
[j15]
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Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia:
GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 969-984 (2022)
2018
[j14]
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Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Huimin Ma, Sanja Fidler, Raquel Urtasun:
3D Object Proposals Using Stereo Imagery for Accurate Object Class Detection. IEEE Trans. Pattern Anal. Mach. Intell. 40(5): 1259-1272 (2018)
[j13]
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Patrick Judd, Jorge Albericio, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger, Raquel Urtasun, Andreas Moshovos:
Proteus: Exploiting precision variability in deep neural networks. Parallel Comput. 73: 40-51 (2018)
2017
[j12]
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  - journals/remotesensing/MerkleLAMU17
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Nina Merkle, Wenjie Luo, Stefan Auer, Rupert Müller, Raquel Urtasun:
Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images. Remote. Sens. 9(6): 586 (2017)
2016
[j11]
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Tamir Hazan, Alexander G. Schwing, Raquel Urtasun:
Blending Learning and Inference in Conditional Random Fields. J. Mach. Learn. Res. 17: 237:1-237:25 (2016)
[j10]
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Roozbeh Mottaghi, Sanja Fidler, Alan L. Yuille, Raquel Urtasun, Devi Parikh:
Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 38(1): 74-87 (2016)
[j9]
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Marcus A. Brubaker, Andreas Geiger, Raquel Urtasun:
Map-Based Probabilistic Visual Self-Localization. IEEE Trans. Pattern Anal. Mach. Intell. 38(4): 652-665 (2016)
2014
[j8]
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Andreas Geiger, Martin Lauer, Christian Wojek, Christoph Stiller, Raquel Urtasun:
3D Traffic Scene Understanding From Movable Platforms. IEEE Trans. Pattern Anal. Mach. Intell. 36(5): 1012-1025 (2014)
2013
[j7]
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Andreas Geiger, Philip Lenz, Christoph Stiller, Raquel Urtasun:
Vision meets robotics: The KITTI dataset. Int. J. Robotics Res. 32(11): 1231-1237 (2013)
2010
[j6]
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  - journals/ijcv/KapoorGUD10
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Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Trevor Darrell:
Gaussian Processes for Object Categorization. Int. J. Comput. Vis. 88(2): 169-188 (2010)
2006
[j5]
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Raquel Urtasun, David J. Fleet, Pascal Fua:
Temporal motion models for monocular and multiview 3D human body tracking. Comput. Vis. Image Underst. 104(2-3): 157-177 (2006)
2005
[j4]
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Lorna Herda, Raquel Urtasun, Pascal Fua:
Hierarchical implicit surface joint limits for human body tracking. Comput. Vis. Image Underst. 99(2): 189-209 (2005)
2004
[j3]
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  - journals/cgf/UrtasunGBTF04
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Raquel Urtasun, Pascal Glardon, Ronan Boulic, Daniel Thalmann, Pascal Fua:
Style-Based Motion Synthesis. Comput. Graph. Forum 23(4): 799-812 (2004)
2003
[j2]
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  - journals/ijrr/HerdaUFH03
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Lorna Herda, Raquel Urtasun, Pascal Fua, Andrew J. Hanson:
Automatic Determination of Shoulder Joint Limits Using Quaternion Field Boundaries. Int. J. Robotics Res. 22(6): 419-438 (2003)
[j1]
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  - journals/pr/DokladalBCRUG03
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Petr Dokládal, Isabelle Bloch, Michel Couprie, Daniel Ruijters, Raquel Urtasun, Line Garnero:
opologically controlled segmentation of 3D magnetic resonance images of the head by using morphological operators. Pattern Recognit. 36(10): 2463-2478 (2003)

Conference and Workshop Papers

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2023
[c239]
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  - conf/corl/ZhangTZWSU23
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Chris Zhang, James Tu, Lunjun Zhang, Kelvin Wong, Simon Suo, Raquel Urtasun:
Learning Realistic Traffic Agents in Closed-loop. CoRL 2023: 800-821
[c238]
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  - conf/corl/SarvaWTXMU23
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Jay Sarva, Jingkang Wang, James Tu, Yuwen Xiong, Sivabalan Manivasagam, Raquel Urtasun:
Adv3D: Generating Safety-Critical 3D Objects through Closed-Loop Simulation. CoRL 2023: 1316-1334
[c237]
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  - conf/corl/AtharL0U23
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Ali Athar, Enxu Li, Sergio Casas, Raquel Urtasun:
4D-Former: Multimodal 4D Panoptic Segmentation. CoRL 2023: 2151-2164
[c236]
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James Tu, Simon Suo, Chris Zhang, Kelvin Wong, Raquel Urtasun:
Towards Scalable Coverage-Based Testing of Autonomous Vehicles. CoRL 2023: 2611-2623
[c235]
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Anqi Joyce Yang, Sergio Casas, Nikita Dvornik, Sean Segal, Yuwen Xiong, Jordan Sir Kwang Hu, Carter Fang, Raquel Urtasun:
LabelFormer: Object Trajectory Refinement for Offboard Perception from LiDAR Point Clouds. CoRL 2023: 3364-3383
[c234]
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  - conf/cvpr/XiongMWU23
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Yuwen Xiong, Wei-Chiu Ma, Jingkang Wang, Raquel Urtasun:
Learning Compact Representations for LiDAR Completion and Generation. CVPR 2023: 1074-1083
[c233]
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  - conf/cvpr/AgroS0U23
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Ben Agro, Quinlan Sykora, Sergio Casas, Raquel Urtasun:
Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving. CVPR 2023: 1379-1388
[c232]
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  - conf/cvpr/00030WMMYU23
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Ze Yang, Yun Chen, Jingkang Wang, Sivabalan Manivasagam, Wei-Chiu Ma, Anqi Joyce Yang, Raquel Urtasun:
UniSim: A Neural Closed-Loop Sensor Simulator. CVPR 2023: 1389-1399
[c231]
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  - conf/cvpr/ZhangYX00RU23
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Lunjun Zhang, Anqi Joyce Yang, Yuwen Xiong, Sergio Casas, Bin Yang, Mengye Ren, Raquel Urtasun:
Towards Unsupervised Object Detection from LiDAR Point Clouds. CVPR 2023: 9317-9328
[c230]
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  - conf/cvpr/SuoWXTC0U23
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Simon Suo, Kelvin Wong, Justin Xu, James Tu, Alexander Cui, Sergio Casas, Raquel Urtasun:
MIXSIM: A Hierarchical Framework for Mixed Reality Traffic Simulation. CVPR 2023: 9622-9631
[c229]
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  - conf/iccv/Li0U23
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Enxu Li, Sergio Casas, Raquel Urtasun:
MemorySeg: Online LiDAR Semantic Segmentation with a Latent Memory. ICCV 2023: 745-754
[c228]
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  - conf/iccv/ManivasagamBW0U23
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Sivabalan Manivasagam, Ioan Andrei Bârsan, Jingkang Wang, Ze Yang, Raquel Urtasun:
Towards Zero Domain Gap: A Comprehensive Study of Realistic LiDAR Simulation for Autonomy Testing. ICCV 2023: 8238-8248
[c227]
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  - conf/iccv/Liu00WMU23
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Jeffrey Yunfan Liu, Yun Chen, Ze Yang, Jingkang Wang, Sivabalan Manivasagam, Raquel Urtasun:
Real-Time Neural Rasterization for Large Scenes. ICCV 2023: 8382-8393
[c226]
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  - conf/icra/CuiCWSU23
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Alexander Cui, Sergio Casas, Kelvin Wong, Simon Suo, Raquel Urtasun:
GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting. ICRA 2023: 7801-7807
[c225]
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  - conf/icra/YangMCWHU23
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Ze Yang, Sivabalan Manivasagam, Yun Chen, Jingkang Wang, Rui Hu, Raquel Urtasun:
Reconstructing Objects in-the-wild for Realistic Sensor Simulation. ICRA 2023: 11661-11668
[c224]
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  - conf/nips/PunSW00MMU23
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Ava Pun, Gary Sun, Jingkang Wang, Yun Chen, Ze Yang, Sivabalan Manivasagam, Wei-Chiu Ma, Raquel Urtasun:
Neural Lighting Simulation for Urban Scenes. NeurIPS 2023
2022
[c223]
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  - conf/corl/WangM00BYMU22
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Jingkang Wang, Sivabalan Manivasagam, Yun Chen, Ze Yang, Ioan Andrei Barsan, Anqi Joyce Yang, Wei-Chiu Ma, Raquel Urtasun:
CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation. CoRL 2022: 630-642
[c222]
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  - conf/cvpr/MaYWU022
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Wei-Chiu Ma, Anqi Joyce Yang, Shenlong Wang, Raquel Urtasun, Antonio Torralba:
Virtual Correspondence: Humans as a Cue for Extreme-View Geometry. CVPR 2022: 15903-15913
[c221]
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Chris Zhang, Runsheng Guo, Wenyuan Zeng, Yuwen Xiong, Binbin Dai, Rui Hu, Mengye Ren, Raquel Urtasun:
Rethinking Closed-Loop Training for Autonomous Driving. ECCV (39) 2022: 264-282
[c220]
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  - conf/wacv/DuggalWMMLWU22
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Shivam Duggal, Zihao Wang, Wei-Chiu Ma, Sivabalan Manivasagam, Justin Liang, Shenlong Wang, Raquel Urtasun:
Mending Neural Implicit Modeling for 3D Vehicle Reconstruction in the Wild. WACV 2022: 277-286
2021
[c219]
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  - conf/corl/SegalK0ZRWU21
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Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun:
Just Label What You Need: Fine-Grained Active Selection for P&P through Partially Labeled Scenes. CoRL 2021: 816-826
[c218]
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  - conf/corl/TuLYR0LBYU21
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James Tu, Huichen Li, Xinchen Yan, Mengye Ren, Yun Chen, Ming Liang, Eilyan Bitar, Ersin Yumer, Raquel Urtasun:
Exploring Adversarial Robustness of Multi-sensor Perception Systems in Self Driving. CoRL 2021: 1013-1024
[c217]
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  - conf/cvpr/TanWWMRU21
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Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
SceneGen: Learning To Generate Realistic Traffic Scenes. CVPR 2021: 892-901
[c216]
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  - conf/cvpr/PhillipsMB0SU21
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John Phillips, Julieta Martinez, Ioan Andrei Barsan, Sergio Casas, Abbas Sadat, Raquel Urtasun:
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction. CVPR 2021: 4679-4689
[c215]
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  - conf/cvpr/0014RDWYMXYU21
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Yun Chen, Frieda Rong, Shivam Duggal, Shenlong Wang, Xinchen Yan, Sivabalan Manivasagam, Shangjie Xue, Ersin Yumer, Raquel Urtasun:
GeoSim: Realistic Video Simulation via Geometry-Aware Composition for Self-Driving. CVPR 2021: 7230-7240
[c214]
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  - conf/cvpr/WangPTMS0RU21
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Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun:
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles. CVPR 2021: 9909-9918
[c213]
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  - conf/cvpr/SuoR0U21
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Simon Suo, Sebastian Regalado, Sergio Casas, Raquel Urtasun:
TrafficSim: Learning To Simulate Realistic Multi-Agent Behaviors. CVPR 2021: 10400-10409
[c212]
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  - conf/cvpr/YangWMHMYYU21
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Ze Yang, Shenlong Wang, Sivabalan Manivasagam, Zeng Huang, Wei-Chiu Ma, Xinchen Yan, Ersin Yumer, Raquel Urtasun:
S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling. CVPR 2021: 13284-13293
[c211]
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  - conf/cvpr/0002SU21
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Sergio Casas, Abbas Sadat, Raquel Urtasun:
MP3: A Unified Model To Map, Perceive, Predict and Plan. CVPR 2021: 14403-14412
[c210]
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  - conf/cvpr/MartinezSLBZU21
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Julieta Martinez, Jashan Shewakramani, Ting-Wei Liu, Ioan Andrei Barsan, Wenyuan Zeng, Raquel Urtasun:
Permute, Quantize, and Fine-Tune: Efficient Compression of Neural Networks. CVPR 2021: 15699-15708
[c209]
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  - conf/iccv/TuWWMRU21
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James Tu, Tsun-Hsuan Wang, Jingkang Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
Adversarial Attacks On Multi-Agent Communication. ICCV 2021: 7748-7757
[c208]
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  - conf/iccv/XiongRZW21
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Yuwen Xiong, Mengye Ren, Wenyuan Zeng, Raquel Urtasun Waabi:
Self-Supervised Representation Learning from Flow Equivariance. ICCV 2021: 10171-10180
[c207]
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  - conf/iccv/Cui0SLU21
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Alexander Cui, Sergio Casas, Abbas Sadat, Renjie Liao, Raquel Urtasun:
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving. ICCV 2021: 16087-16096
[c206]
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  - conf/iclr/LiaoUZ21
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Renjie Liao, Raquel Urtasun, Richard S. Zemel:
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks. ICLR 2021
[c205]
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  - conf/icra/WeiRZLYU21
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Bob Wei, Mengye Ren, Wenyuan Zeng, Ming Liang, Bin Yang, Raquel Urtasun:
Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving. ICRA 2021: 4875-4881
[c204]
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  - conf/icra/LiuZUY21
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Jerry Liu, Wenyuan Zeng, Raquel Urtasun, Ersin Yumer:
Deep Structured Reactive Planning. ICRA 2021: 4897-4904
[c203]
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  - conf/icra/YangCBUW21
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Anqi Joyce Yang, Can Cui, Ioan Andrei Bârsan, Raquel Urtasun, Shenlong Wang:
Asynchronous Multi-View SLAM. ICRA 2021: 5669-5676
[c202]
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Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun:
LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting. IROS 2021: 532-539
[c201]
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Katie Luo, Sergio Casas, Renjie Liao, Xinchen Yan, Yuwen Xiong, Wenyuan Zeng, Raquel Urtasun:
Safety-Oriented Pedestrian Occupancy Forecasting. IROS 2021: 1015-1022
[c200]
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Yan Wang, Bin Yang, Rui Hu, Ming Liang, Raquel Urtasun:
PLUMENet: Efficient 3D Object Detection from Stereo Images. IROS 2021: 3383-3390
[c199]
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  - conf/iros/SadatS0T0UY21
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Abbas Sadat, Sean Segal, Sergio Casas, James Tu, Bin Yang, Raquel Urtasun, Ersin Yumer:
Diverse Complexity Measures for Dataset Curation in Self-Driving. IROS 2021: 8609-8616
[c198]
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Xiaohui Zeng, Raquel Urtasun, Richard S. Zemel, Sanja Fidler, Renjie Liao:
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation. UAI 2021: 1089-1099
2020
[c197]
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Meet Shah, Zhiling Huang, Ankit Laddha, Matthew Langford, Blake Barber, Sida Zhang, Carlos Vallespi-Gonzalez, Raquel Urtasun:
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion. CoRL 2020: 31-48
[c196]
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Ze Yang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
Recovering and Simulating Pedestrians in the Wild. CoRL 2020: 419-431
[c195]
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Sean Segal, Eric Kee, Wenjie Luo, Abbas Sadat, Ersin Yumer, Raquel Urtasun:
Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs. CoRL 2020: 973-983
[c194]
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Davi Frossard, Shun Da Suo, Sergio Casas, James Tu, Raquel Urtasun:
StrObe: Streaming Object Detection from LiDAR Packets. CoRL 2020: 1174-1183
[c193]
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Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun:
Learning to Communicate and Correct Pose Errors. CoRL 2020: 1195-1210
[c192]
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  - conf/cvpr/HuangWWLU20
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Lila Huang, Shenlong Wang, Kelvin Wong, Jerry Liu, Raquel Urtasun:
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression. CVPR 2020: 1310-1320
[c191]
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Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Yuwen Xiong, Rui Hu, Raquel Urtasun:
PolyTransform: Deep Polygon Transformer for Instance Segmentation. CVPR 2020: 9128-9137
[c190]
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Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Shuhan Tan, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World. CVPR 2020: 11164-11173
[c189]
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Ming Liang, Bin Yang, Wenyuan Zeng, Yun Chen, Rui Hu, Sergio Casas, Raquel Urtasun:
PnPNet: End-to-End Perception and Prediction With Tracking in the Loop. CVPR 2020: 11550-11559
[c188]
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James Tu, Mengye Ren, Sivabalan Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun:
Physically Realizable Adversarial Examples for LiDAR Object Detection. CVPR 2020: 13713-13722
[c187]
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  - conf/eccv/ZengWLCYU20
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Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun:
DSDNet: Deep Structured Self-driving Network. ECCV (21) 2020: 156-172
[c186]
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Ze Yang, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Liwei Wang, Stephen Lin, Han Hu:
Dense RepPoints: Representing Visual Objects with Dense Point Sets. ECCV (21) 2020: 227-244
[c185]
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Wei-Chiu Ma, Shenlong Wang, Jiayuan Gu, Sivabalan Manivasagam, Antonio Torralba, Raquel Urtasun:
Deep Feedback Inverse Problem Solver. ECCV (5) 2020: 229-246
[c184]
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Jiayuan Gu, Wei-Chiu Ma, Sivabalan Manivasagam, Wenyuan Zeng, Zihao Wang, Yuwen Xiong, Hao Su, Raquel Urtasun:
Weakly-Supervised 3D Shape Completion in the Wild. ECCV (5) 2020: 283-299
[c183]
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Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun:
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction. ECCV (26) 2020: 312-329
[c182]
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  - conf/eccv/SadatCRWDU20
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Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, Raquel Urtasun:
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations. ECCV (23) 2020: 414-430
[c181]
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  - conf/eccv/LiuWMSHDU20
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Jerry Liu, Shenlong Wang, Wei-Chiu Ma, Meet Shah, Rui Hu, Pranaab Dhawan, Raquel Urtasun:
Conditional Entropy Coding for Efficient Video Compression. ECCV (17) 2020: 453-468
[c180]
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Bin Yang, Runsheng Guo, Ming Liang, Sergio Casas, Raquel Urtasun:
RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects. ECCV (18) 2020: 496-512
[c179]
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Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun:
Learning Lane Graph Representations for Motion Forecasting. ECCV (2) 2020: 541-556
[c178]
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  - conf/eccv/HomayounfarXLMU20
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Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun:
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation. ECCV (23) 2020: 555-571
[c177]
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Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wenyuan Zeng, Raquel Urtasun:
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction. ECCV (2) 2020: 605-621
[c176]
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Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun:
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting. ECCV (23) 2020: 624-641
[c175]
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  - conf/icml/LimUY20
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Cong Han Lim, Raquel Urtasun, Ersin Yumer:
Hierarchical Verification for Adversarial Robustness. ICML 2020: 6072-6082
[c174]
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Quinlan Sykora, Mengye Ren, Raquel Urtasun:
Multi-Agent Routing Value Iteration Network. ICML 2020: 9300-9310
[c173]
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  - conf/icra/0002GLU20
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Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun:
SpAGNN: Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data. ICRA 2020: 9491-9497
[c172]
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Sergio Casas, Cole Gulino, Simon Suo, Raquel Urtasun:
The Importance of Prior Knowledge in Precise Multimodal Prediction. IROS 2020: 2295-2302
[c171]
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  - conf/iros/MartinezDFBWMU20
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Julieta Martinez, Sasha Doubov, Jack Fan, Ioan Andrei Bârsan, Shenlong Wang, Gellért Máttyus, Raquel Urtasun:
Pit30M: A Benchmark for Global Localization in the Age of Self-Driving Cars. IROS 2020: 4477-4484
[c170]
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Lingyun Luke Li, Bin Yang, Ming Liang, Wenyuan Zeng, Mengye Ren, Sean Segal, Raquel Urtasun:
End-to-end Contextual Perception and Prediction with Interaction Transformer. IROS 2020: 5784-5791
[c169]
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  - conf/nips/BiswasLWWU20
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Sourav Biswas, Jerry Liu, Kelvin Wong, Shenlong Wang, Raquel Urtasun:
MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models. NeurIPS 2020
[c168]
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Yuwen Xiong, Mengye Ren, Raquel Urtasun:
LoCo: Local Contrastive Representation Learning. NeurIPS 2020
2019
[c167]
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  - conf/acssc/YoonLXZFUZP19
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KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow:
Inference in Probabilistic Graphical Models by Graph Neural Networks. ACSSC 2019: 868-875
[c166]
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  - conf/corl/WongWRLU19
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Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun:
Identifying Unknown Instances for Autonomous Driving. CoRL 2019: 384-393
[c165]
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Ajay Jain, Sergio Casas, Renjie Liao, Yuwen Xiong, Song Feng, Sean Segal, Raquel Urtasun:
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction. CoRL 2019: 407-419
[c164]
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  - conf/cvpr/MaWHXU19
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Wei-Chiu Ma, Shenlong Wang, Rui Hu, Yuwen Xiong, Raquel Urtasun:
Deep Rigid Instance Scene Flow. CVPR 2019: 3614-3622
[c163]
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  - conf/cvpr/LiangYCHU19
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Ming Liang, Bin Yang, Yun Chen, Rui Hu, Raquel Urtasun:
Multi-Task Multi-Sensor Fusion for 3D Object Detection. CVPR 2019: 7345-7353
[c162]
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  - conf/cvpr/ChengLFU19
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Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun:
DARNet: Deep Active Ray Network for Building Segmentation. CVPR 2019: 7431-7439
[c161]
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  - conf/cvpr/ZengLSSYCU19
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Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun:
End-To-End Interpretable Neural Motion Planner. CVPR 2019: 8660-8669
[c160]
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  - conf/cvpr/XiongLZHBYU19
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Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun:
UPSNet: A Unified Panoptic Segmentation Network. CVPR 2019: 8818-8826
[c159]
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  - conf/cvpr/LiangHMWU19
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Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Shenlong Wang, Raquel Urtasun:
Convolutional Recurrent Network for Road Boundary Extraction. CVPR 2019: 9512-9521
[c158]
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  - conf/cvpr/WeiBWMU19
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Xinkai Wei, Ioan Andrei Barsan, Shenlong Wang, Julieta Martinez, Raquel Urtasun:
Learning to Localize Through Compressed Binary Maps. CVPR 2019: 10316-10324
[c157]
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  - conf/iccv/HomayounfarLMFW19
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Namdar Homayounfar, Justin Liang, Wei-Chiu Ma, Jack Fan, Xinyu Wu, Raquel Urtasun:
DAGMapper: Learning to Map by Discovering Lane Topology. ICCV 2019: 2911-2920
[c156]
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  - conf/iccv/LiuWU19
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Jerry Liu, Shenlong Wang, Raquel Urtasun:
DSIC: Deep Stereo Image Compression. ICCV 2019: 3136-3145
[c155]
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  - conf/iccv/ZengLGXFU19
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Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun:
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation. ICCV 2019: 3928-3937
[c154]
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  - conf/iccv/DuggalWMHU19
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Shivam Duggal, Shenlong Wang, Wei-Chiu Ma, Rui Hu, Raquel Urtasun:
DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch. ICCV 2019: 4383-4392
[c153]
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  - conf/iccv/ChenYLU19
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Yun Chen, Bin Yang, Ming Liang, Raquel Urtasun:
Learning Joint 2D-3D Representations for Depth Completion. ICCV 2019: 10022-10031
[c152]
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  - conf/iclr/LawSFUZ19
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Marc T. Law, Jake Snell, Amir-massoud Farahmand, Raquel Urtasun, Richard S. Zemel:
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models. ICLR (Poster) 2019
[c151]
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Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel:
LanczosNet: Multi-Scale Deep Graph Convolutional Networks. ICLR (Poster) 2019
[c150]
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Chris Zhang, Mengye Ren, Raquel Urtasun:
Graph HyperNetworks for Neural Architecture Search. ICLR (Poster) 2019
[c149]
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  - conf/icra/FrossardKU19
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Davi Frossard, Eric Kee, Raquel Urtasun:
DeepSignals: Predicting Intent of Drivers Through Visual Signals. ICRA 2019: 9697-9703
[c148]
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  - conf/iros/SadatRPLYU19
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Abbas Sadat, Mengye Ren, Andrei Pokrovsky, Yen-Chen Lin, Ersin Yumer, Raquel Urtasun:
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles. IROS 2019: 3949-3956
[c147]
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Wei-Chiu Ma, Raquel Urtasun, Ignacio Tartavull, Ioan Andrei Bârsan, Shenlong Wang, Min Bai, Gellért Máttyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky:
Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization. IROS 2019: 5304-5311
[c146]
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Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel:
Efficient Graph Generation with Graph Recurrent Attention Networks. NeurIPS 2019: 4257-4267
2018
[c145]
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Chris Zhang, Wenjie Luo, Raquel Urtasun:
Efficient Convolutions for Real-Time Semantic Segmentation of 3D Point Clouds. 3DV 2018: 399-408
[c144]
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Bin Yang, Ming Liang, Raquel Urtasun:
HDNET: Exploiting HD Maps for 3D Object Detection. CoRL 2018: 146-155
[c143]
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Ioan Andrei Barsan, Shenlong Wang, Andrei Pokrovsky, Raquel Urtasun:
Learning to Localize Using a LiDAR Intensity Map. CoRL 2018: 605-616
[c142]
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Sergio Casas, Wenjie Luo, Raquel Urtasun:
IntentNet: Learning to Predict Intention from Raw Sensor Data. CoRL 2018: 947-956
[c141]
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Xiaojuan Qi, Renjie Liao, Zhengzhe Liu, Raquel Urtasun, Jiaya Jia:
GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation. CVPR 2018: 283-291
[c140]
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Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, Raquel Urtasun:
Deep Parametric Continuous Convolutional Neural Networks. CVPR 2018: 2589-2597
[c139]
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Hang Chu, Wei-Chiu Ma, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
SurfConv: Bridging 3D and 2D Convolution for RGBD Images. CVPR 2018: 3002-3011
[c138]
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Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun:
Hierarchical Recurrent Attention Networks for Structured Online Maps. CVPR 2018: 3417-3426
[c137]
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Wenjie Luo, Bin Yang, Raquel Urtasun:
Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting With a Single Convolutional Net. CVPR 2018: 3569-3577
[c136]
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Bin Yang, Wenjie Luo, Raquel Urtasun:
PIXOR: Real-Time 3D Object Detection From Point Clouds. CVPR 2018: 7652-7660
[c135]
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Gellért Máttyus, Raquel Urtasun:
Matching Adversarial Networks. CVPR 2018: 8024-8032
[c134]
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Mengye Ren, Andrei Pokrovsky, Bin Yang, Raquel Urtasun:
SBNet: Sparse Blocks Network for Fast Inference. CVPR 2018: 8711-8720
[c133]
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  - conf/cvpr/MarcosTKZBLU18
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Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun:
Learning Deep Structured Active Contours End-to-End. CVPR 2018: 8877-8885
[c132]
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Wei-Chiu Ma, Hang Chu, Bolei Zhou, Raquel Urtasun, Antonio Torralba:
Single Image Intrinsic Decomposition Without a Single Intrinsic Image. ECCV (14) 2018: 211-229
[c131]
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Justin Liang, Raquel Urtasun:
End-to-End Deep Structured Models for Drawing Crosswalks. ECCV (12) 2018: 407-423
[c130]
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Ming Liang, Bin Yang, Shenlong Wang, Raquel Urtasun:
Deep Continuous Fusion for Multi-sensor 3D Object Detection. ECCV (16) 2018: 663-678
[c129]
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Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel:
Graph Partition Neural Networks for Semi-Supervised Classification. ICLR (Workshop) 2018
[c128]
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KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow:
Inference in probabilistic graphical models by Graph Neural Networks. ICLR (Workshop) 2018
[c127]
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Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Raquel Urtasun, Richard S. Zemel:
Leveraging Constraint Logic Programming for Neural Guided Program Synthesis. ICLR (Workshop) 2018
[c126]
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Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel:
Reviving and Improving Recurrent Back-Propagation. ICML 2018: 3088-3097
[c125]
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Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun:
Learning to Reweight Examples for Robust Deep Learning. ICML 2018: 4331-4340
[c124]
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Davi Frossard, Raquel Urtasun:
End-to-end Learning of Multi-sensor 3D Tracking by Detection. ICRA 2018: 635-642
[c123]
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Min Bai, Gellért Máttyus, Namdar Homayounfar, Shenlong Wang, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun:
Deep Multi-Sensor Lane Detection. IROS 2018: 3102-3109
[c122]
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  - conf/ivs/TeichmannWZCU18
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Marvin Teichmann, Michael Weber, J. Marius Zöllner, Roberto Cipolla, Raquel Urtasun:
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving. Intelligent Vehicles Symposium 2018: 1013-1020
[c121]
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Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel:
Neural Guided Constraint Logic Programming for Program Synthesis. NeurIPS 2018: 1744-1753
2017
[c120]
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Min Bai, Raquel Urtasun:
Deep Watershed Transform for Instance Segmentation. CVPR 2017: 2858-2866
[c119]
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Namdar Homayounfar, Sanja Fidler, Raquel Urtasun:
Sports Field Localization via Deep Structured Models. CVPR 2017: 4012-4020
[c118]
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  - conf/cvpr/CastrejonKUF17
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Lluís Castrejón, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
Annotating Object Instances with a Polygon-RNN. CVPR 2017: 4485-4493
[c117]
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Marc T. Law, Yaoliang Yu, Raquel Urtasun, Richard S. Zemel, Eric P. Xing:
Efficient Multiple Instance Metric Learning Using Weakly Supervised Data. CVPR 2017: 5948-5956
[c116]
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  - conf/iccv/ZhuFULL17
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Shizhan Zhu, Sanja Fidler, Raquel Urtasun, Dahua Lin, Chen Change Loy:
Be Your Own Prada: Fashion Synthesis with Structural Coherence. ICCV 2017: 1689-1697
[c115]
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Bo Dai, Sanja Fidler, Raquel Urtasun, Dahua Lin:
Towards Diverse and Natural Image Descriptions via a Conditional GAN. ICCV 2017: 2989-2998
[c114]
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Shenlong Wang, Min Bai, Gellért Máttyus, Hang Chu, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun:
TorontoCity: Seeing the World with a Million Eyes. ICCV 2017: 3028-3036
[c113]
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Gellért Máttyus, Wenjie Luo, Raquel Urtasun:
DeepRoadMapper: Extracting Road Topology from Aerial Images. ICCV 2017: 3458-3466
[c112]
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Shu Liu, Jiaya Jia, Sanja Fidler, Raquel Urtasun:
SGN: Sequential Grouping Networks for Instance Segmentation. ICCV 2017: 3516-3524
[c111]
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  - conf/iccv/LiTLJUF17
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Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler:
Situation Recognition with Graph Neural Networks. ICCV 2017: 4183-4192
[c110]
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Xiaojuan Qi, Renjie Liao, Jiaya Jia, Sanja Fidler, Raquel Urtasun:
3D Graph Neural Networks for RGBD Semantic Segmentation. ICCV 2017: 5209-5218
[c109]
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Eugene Belilovsky, Matthew B. Blaschko, Jamie Ryan Kiros, Raquel Urtasun, Richard S. Zemel:
Joint Embeddings of Scene Graphs and Images. ICLR (Workshop) 2017
[c108]
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Hang Chu, Raquel Urtasun, Sanja Fidler:
Song From PI: A Musically Plausible Network for Pop Music Generation. ICLR (Workshop) 2017
[c107]
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Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel:
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. ICLR (Poster) 2017
[c106]
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Marc T. Law, Raquel Urtasun, Richard S. Zemel:
Deep Spectral Clustering Learning. ICML 2017: 1985-1994
[c105]
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Wei-Chiu Ma, Shenlong Wang, Marcus A. Brubaker, Sanja Fidler, Raquel Urtasun:
Find your way by observing the sun and other semantic cues. ICRA 2017: 6292-6299
[c104]
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  - conf/nips/GomezRUG17
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Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse:
The Reversible Residual Network: Backpropagation Without Storing Activations. NIPS 2017: 2214-2224
[c103]
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Eleni Triantafillou, Richard S. Zemel, Raquel Urtasun:
Few-Shot Learning Through an Information Retrieval Lens. NIPS 2017: 2255-2265
2016
[c102]
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Yali Wang, Marcus A. Brubaker, Brahim Chaib-draa, Raquel Urtasun:
Sequential Inference for Deep Gaussian Process. AISTATS 2016: 694-703
[c101]
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Raquel Urtasun:
Towards Affordable Self-driving Cars. BMVC 2016
[c100]
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Ziyu Zhang, Sanja Fidler, Raquel Urtasun:
Instance-Level Segmentation for Autonomous Driving with Deep Densely Connected MRFs. CVPR 2016: 669-677
[c99]
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Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang, Huimin Ma, Sanja Fidler, Raquel Urtasun:
Monocular 3D Object Detection for Autonomous Driving. CVPR 2016: 2147-2156
[c98]
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  - conf/cvpr/MattyusWFU16
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Gellért Máttyus, Shenlong Wang, Sanja Fidler, Raquel Urtasun:
HD Maps: Fine-Grained Road Segmentation by Parsing Ground and Aerial Images. CVPR 2016: 3611-3619
[c97]
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Makarand Tapaswi, Yukun Zhu, Rainer Stiefelhagen, Antonio Torralba, Raquel Urtasun, Sanja Fidler:
MovieQA: Understanding Stories in Movies through Question-Answering. CVPR 2016: 4631-4640
[c96]
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Wenjie Luo, Alexander G. Schwing, Raquel Urtasun:
Efficient Deep Learning for Stereo Matching. CVPR 2016: 5695-5703
[c95]
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Min Bai, Wenjie Luo, Kaustav Kundu, Raquel Urtasun:
Exploiting Semantic Information and Deep Matching for Optical Flow. ECCV (6) 2016: 154-170
[c94]
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Hang Chu, Shenlong Wang, Raquel Urtasun, Sanja Fidler:
HouseCraft: Building Houses from Rental Ads and Street Views. ECCV (6) 2016: 500-516
[c93]
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Yang Song, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun:
Training Deep Neural Networks via Direct Loss Minimization. ICML 2016: 2169-2177
[c92]
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Shenlong Wang, Sanja Fidler, Raquel Urtasun:
Proximal Deep Structured Models. NIPS 2016: 865-873
[c91]
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Wenjie Luo, Yujia Li, Raquel Urtasun, Richard S. Zemel:
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks. NIPS 2016: 4898-4906
[c90]
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Renjie Liao, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun:
Learning Deep Parsimonious Representations. NIPS 2016: 5076-5084
[c89]
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Eleni Triantafillou, Jamie Ryan Kiros, Raquel Urtasun, Richard S. Zemel:
Towards Generalizable Sentence Embeddings. Rep4NLP@ACL 2016: 239-248
[c88]
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Ivan Vendrov, Ryan Kiros, Sanja Fidler, Raquel Urtasun:
Order-Embeddings of Images and Language. ICLR 2016
2015
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Dahua Lin, Sanja Fidler, Chen Kong, Raquel Urtasun:
Generating Multi-sentence Natural Language Descriptions of Indoor Scenes. BMVC 2015: 93.1-93.13
[c86]
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Edgar Simo-Serra, Sanja Fidler, Francesc Moreno-Noguer, Raquel Urtasun:
Neuroaesthetics in fashion: Modeling the perception of fashionability. CVPR 2015: 869-877
[c85]
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Jian Yao, Marko Boben, Sanja Fidler, Raquel Urtasun:
Real-time coarse-to-fine topologically preserving segmentation. CVPR 2015: 2947-2955
[c84]
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Chenxi Liu, Alexander G. Schwing, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
Rent3D: Floor-plan priors for monocular layout estimation. CVPR 2015: 3413-3421
[c83]
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Jia Xu, Alexander G. Schwing, Raquel Urtasun:
Learning to segment under various forms of weak supervision. CVPR 2015: 3781-3790
[c82]
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Shenlong Wang, Sanja Fidler, Raquel Urtasun:
Holistic 3D scene understanding from a single geo-tagged image. CVPR 2015: 3964-3972
[c81]
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Yukun Zhu, Raquel Urtasun, Ruslan Salakhutdinov, Sanja Fidler:
segDeepM: Exploiting segmentation and context in deep neural networks for object detection. CVPR 2015: 4703-4711
[c80]
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Yukun Zhu, Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books. ICCV 2015: 19-27
[c79]
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Gellért Máttyus, Shenlong Wang, Sanja Fidler, Raquel Urtasun:
Enhancing Road Maps by Parsing Aerial Images Around the World. ICCV 2015: 1689-1697
[c78]
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Ziyu Zhang, Alexander G. Schwing, Sanja Fidler, Raquel Urtasun:
Monocular Object Instance Segmentation and Depth Ordering with CNNs. ICCV 2015: 2614-2622
[c77]
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Shenlong Wang, Sanja Fidler, Raquel Urtasun:
Lost Shopping! Monocular Localization in Large Indoor Spaces. ICCV 2015: 2695-2703
[c76]
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Philip Lenz, Andreas Geiger, Raquel Urtasun:
FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation. ICCV 2015: 4364-4372
[c75]
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Liang-Chieh Chen, Alexander G. Schwing, Alan L. Yuille, Raquel Urtasun:
Learning Deep Structured Models. ICML 2015: 1785-1794
[c74]
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Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew G. Berneshawi, Huimin Ma, Sanja Fidler, Raquel Urtasun:
3D Object Proposals for Accurate Object Class Detection. NIPS 2015: 424-432
[c73]
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Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Skip-Thought Vectors. NIPS 2015: 3294-3302
[c72]
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Jian Yao, Srikumar Ramalingam, Yuichi Taguchi, Yohei Miki, Raquel Urtasun:
Estimating Drivable Collision-Free Space from Monocular Video. WACV 2015: 420-427
[c71]
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Liang-Chieh Chen, Alexander G. Schwing, Alan L. Yuille, Raquel Urtasun:
Learning Deep Structured Models. ICLR (Workshop) 2015
2014
[c70]
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Edgar Simo-Serra, Sanja Fidler, Francesc Moreno-Noguer, Raquel Urtasun:
A High Performance CRF Model for Clothes Parsing. ACCV (3) 2014: 64-81
[c69]
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Roozbeh Mottaghi, Xianjie Chen, Xiaobai Liu, Nam-Gyu Cho, Seong-Whan Lee, Sanja Fidler, Raquel Urtasun, Alan L. Yuille:
The Role of Context for Object Detection and Semantic Segmentation in the Wild. CVPR 2014: 891-898
[c68]
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Xianjie Chen, Roozbeh Mottaghi, Xiaobai Liu, Sanja Fidler, Raquel Urtasun, Alan L. Yuille:
Detect What You Can: Detecting and Representing Objects Using Holistic Models and Body Parts. CVPR 2014: 1979-1986
[c67]
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Dahua Lin, Sanja Fidler, Chen Kong, Raquel Urtasun:
Visual Semantic Search: Retrieving Videos via Complex Textual Queries. CVPR 2014: 2657-2664
[c66]
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Jia Xu, Alexander G. Schwing, Raquel Urtasun:
Tell Me What You See and I Will Show You Where It Is. CVPR 2014: 3190-3197
[c65]
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Liang-Chieh Chen, Sanja Fidler, Raquel Urtasun:
Beat the MTurkers: Automatic Image Labeling from Weak 3D Supervision. CVPR 2014: 3198-3205
[c64]
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Chen Kong, Dahua Lin, Mohit Bansal, Raquel Urtasun, Sanja Fidler:
What Are You Talking About? Text-to-Image Coreference. CVPR 2014: 3558-3565
[c63]
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Koichiro Yamaguchi, David A. McAllester, Raquel Urtasun:
Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation. ECCV (5) 2014: 756-771
[c62]
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Shenlong Wang, Lei Zhang, Raquel Urtasun:
Transductive Gaussian processes for image denoising. ICCP 2014: 1-8
[c61]
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Alexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun:
Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm. ICML 2014: 487-495
[c60]
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Shenlong Wang, Alexander G. Schwing, Raquel Urtasun:
Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials. NIPS 2014: 936-944
[c59]
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Jian Zhang, Alexander G. Schwing, Raquel Urtasun:
Message Passing Inference for Large Scale Graphical Models with High Order Potentials. NIPS 2014: 1134-1142
[c58]
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Yali Wang, Marcus A. Brubaker, Brahim Chaib-draa, Raquel Urtasun:
Bayesian Filtering with Online Gaussian Process Latent Variable Models. UAI 2014: 849-857
2013
[c57]
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Koichiro Yamaguchi, David A. McAllester, Raquel Urtasun:
Robust Monocular Epipolar Flow Estimation. CVPR 2013: 1862-1869
[c56]
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Sanja Fidler, Abhishek Sharma, Raquel Urtasun:
A Sentence Is Worth a Thousand Pixels. CVPR 2013: 1995-2002
[c55]
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  - conf/cvpr/BrubakerGU13
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Marcus A. Brubaker, Andreas Geiger, Raquel Urtasun:
Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization. CVPR 2013: 3057-3064
[c54]
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  - conf/cvpr/MottaghiFYUP13
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Roozbeh Mottaghi, Sanja Fidler, Jian Yao, Raquel Urtasun, Devi Parikh:
Analyzing Semantic Segmentation Using Hybrid Human-Machine CRFs. CVPR 2013: 3143-3150
[c53]
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Sanja Fidler, Roozbeh Mottaghi, Alan L. Yuille, Raquel Urtasun:
Bottom-Up Segmentation for Top-Down Detection. CVPR 2013: 3294-3301
[c52]
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Alexander G. Schwing, Sanja Fidler, Marc Pollefeys, Raquel Urtasun:
Box in the Box: Joint 3D Layout and Object Reasoning from Single Images. ICCV 2013: 353-360
[c51]
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Jian Zhang, Chen Kan, Alexander G. Schwing, Raquel Urtasun:
Estimating the 3D Layout of Indoor Scenes and Its Clutter from Depth Sensors. ICCV 2013: 1273-1280
[c50]
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Dahua Lin, Sanja Fidler, Raquel Urtasun:
Holistic Scene Understanding for 3D Object Detection with RGBD Cameras. ICCV 2013: 1417-1424
[c49]
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Hongyi Zhang, Andreas Geiger, Raquel Urtasun:
Understanding High-Level Semantics by Modeling Traffic Patterns. ICCV 2013: 3056-3063
[c48]
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Wenjie Luo, Alexander G. Schwing, Raquel Urtasun:
Latent Structured Active Learning. NIPS 2013: 728-736
2012
[c47]
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Jian Yao, Sanja Fidler, Raquel Urtasun:
Describing the scene as a whole: Joint object detection, scene classification and semantic segmentation. CVPR 2012: 702-709
[c46]
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  - conf/cvpr/VarolSFU12
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Aydin Varol, Mathieu Salzmann, Pascal Fua, Raquel Urtasun:
A constrained latent variable model. CVPR 2012: 2248-2255
[c45]
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Alexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun:
Efficient structured prediction for 3D indoor scene understanding. CVPR 2012: 2815-2822
[c44]
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Andreas Geiger, Philip Lenz, Raquel Urtasun:
Are we ready for autonomous driving? The KITTI vision benchmark suite. CVPR 2012: 3354-3361
[c43]
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Koichiro Yamaguchi, Tamir Hazan, David A. McAllester, Raquel Urtasun:
Continuous Markov Random Fields for Robust Stereo Estimation. ECCV (5) 2012: 45-58
[c42]
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Mathieu Salzmann, Raquel Urtasun:
Beyond Feature Points: Structured Prediction for Monocular Non-rigid 3D Reconstruction. ECCV (4) 2012: 245-259
[c41]
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Alexander G. Schwing, Raquel Urtasun:
Efficient Exact Inference for 3D Indoor Scene Understanding. ECCV (6) 2012: 299-313
[c40]
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Alexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun:
Efficient Structured Prediction with Latent Variables for General Graphical Models. ICML 2012
[c39]
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Sanja Fidler, Sven J. Dickinson, Raquel Urtasun:
3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model. NIPS 2012: 620-628
[c38]
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Alexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun:
Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins. NIPS 2012: 2393-2401
[c37]
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Marcus A. Brubaker, Mathieu Salzmann, Raquel Urtasun:
A Family of MCMC Methods on Implicitly Defined Manifolds. AISTATS 2012: 161-172
2011
[c36]
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Alexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun:
Distributed message passing for large scale graphical models. CVPR 2011: 1833-1840
[c35]
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Andreas Geiger, Martin Lauer, Raquel Urtasun:
A generative model for 3D urban scene understanding from movable platforms. CVPR 2011: 1945-1952
[c34]
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  - conf/cvpr/ShyrDJU11
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Alex Shyr, Trevor Darrell, Michael I. Jordan, Raquel Urtasun:
Supervised hierarchical Pitman-Yor process for natural scene segmentation. CVPR 2011: 2281-2288
[c33]
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Henning Hamer, Juergen Gall, Raquel Urtasun, Luc Van Gool:
Data-driven animation of hand-object interactions. FG 2011: 360-367
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Mathieu Salzmann, Raquel Urtasun:
Physically-based motion models for 3D tracking: A convex formulation. ICCV 2011: 2064-2071
[c31]
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Jian Peng, Tamir Hazan, David A. McAllester, Raquel Urtasun:
Convex Max-Product over Compact Sets for Protein Folding. ICML 2011: 729-736
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Angela Yao, Juergen Gall, Luc Van Gool, Raquel Urtasun:
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities. NIPS 2011: 1359-1367
[c29]
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Andreas Geiger, Christian Wojek, Raquel Urtasun:
Joint 3D Estimation of Objects and Scene Layout. NIPS 2011: 1467-1475
2010
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Andreas Geiger, Martin Roser, Raquel Urtasun:
Efficient Large-Scale Stereo Matching. ACCV (1) 2010: 25-38
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Mathieu Salzmann, Raquel Urtasun:
Combining discriminative and generative methods for 3D deformable surface and articulated pose reconstruction. CVPR 2010: 647-654
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Alex Shyr, Raquel Urtasun, Michael I. Jordan:
Sufficient dimension reduction for visual sequence classification. CVPR 2010: 3610-3617
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C. Mario Christoudias, Raquel Urtasun, Mathieu Salzmann, Trevor Darrell:
Learning to Recognize Objects from Unseen Modalities. ECCV (1) 2010: 677-691
[c24]
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Tamir Hazan, Raquel Urtasun:
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction. NIPS 2010: 838-846
[c23]
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Taehwan Kim, Gregory Shakhnarovich, Raquel Urtasun:
Sparse Coding for Learning Interpretable Spatio-Temporal Primitives. NIPS 2010: 1117-1125
[c22]
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Mathieu Salzmann, Raquel Urtasun:
Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation. NIPS 2010: 2065-2073
[c21]
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Mathieu Salzmann, Carl Henrik Ek, Raquel Urtasun, Trevor Darrell:
Factorized Orthogonal Latent Spaces. AISTATS 2010: 701-708
2009
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Andreas Geiger, Raquel Urtasun, Trevor Darrell:
Rank priors for continuous non-linear dimensionality reduction. CVPR 2009: 880-887
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C. Mario Christoudias, Raquel Urtasun, Ashish Kapoor, Trevor Darrell:
Co-training with noisy perceptual observations. CVPR 2009: 2844-2851
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  - conf/icml/LawrenceU09
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Neil D. Lawrence, Raquel Urtasun:
Non-linear matrix factorization with Gaussian processes. ICML 2009: 601-608
2008
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C. Mario Christoudias, Raquel Urtasun, Trevor Darrell:
Unsupervised feature selection via distributed coding for multi-view object recognition. CVPR 2008
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Mathieu Salzmann, Raquel Urtasun, Pascal Fua:
Local deformation models for monocular 3D shape recovery. CVPR 2008
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Raquel Urtasun, Trevor Darrell:
Sparse probabilistic regression for activity-independent human pose inference. CVPR 2008
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Raquel Urtasun, David J. Fleet, Andreas Geiger, Jovan Popovic, Trevor Darrell, Neil D. Lawrence:
Topologically-constrained latent variable models. ICML 2008: 1080-1087
2007
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David Demirdjian, Raquel Urtasun:
Patch-Based Pose Inference with a Mixture of Density Estimators. AMFG 2007: 96-108
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Raquel Urtasun, David J. Fleet, Neil D. Lawrence:
Modeling Human Locomotion with Topologically Constrained Latent Variable Models. Workshop on Human Motion 2007: 104-118
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Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Trevor Darrell:
Active Learning with Gaussian Processes for Object Categorization. ICCV 2007: 1-8
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Raquel Urtasun, Trevor Darrell:
Discriminative Gaussian process latent variable model for classification. ICML 2007: 927-934
2006
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Raquel Urtasun, David J. Fleet, Pascal Fua:
3D People Tracking with Gaussian Process Dynamical Models. CVPR (1) 2006: 238-245
2005
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Raquel Urtasun, David J. Fleet, Pascal Fua:
Monocular 3-D Tracking of the Golf Swing. CVPR (2) 2005: 932-938
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Raquel Urtasun, David J. Fleet, Pascal Fua:
Monocular 3D Tracking of the Golf Swing. CVPR (2) 2005: 1199
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Raquel Urtasun, David J. Fleet, Aaron Hertzmann, Pascal Fua:
Priors for People Tracking from Small Training Sets. ICCV 2005: 403-410
2004
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Raquel Urtasun, Pascal Fua:
3D Human Body Tracking Using Deterministic Temporal Motion Models. ECCV (3) 2004: 92-106
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Lorna Herda, Raquel Urtasun, Pascal Fua:
Hierarchical Implicit Surface Joint Limits to Constrain Video-Based Motion Capture. ECCV (2) 2004: 405-418
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Raquel Urtasun, Pascal Fua:
3D Tracking for Gait Characterization and Recognition. FGR 2004: 17-22
2002
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Lorna Herda, Raquel Urtasun, Pascal Fua, Andrew J. Hanson:
An Automatic Method For Determining Quaternion Field Boundaries for Ball-and-Socket Joint Limits. FGR 2002: 95-100
2001
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Petr Dokládal, Raquel Urtasun, Isabelle Bloch, Line Garnero:
Segmentation of 3D head MR images using morphological reconstruction under constraints and automatic selection of markers. ICIP (3) 2001: 1075-1078

Informal and Other Publications

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What is the meaning of the colors in the publication lists?

2024
[i153]
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Sourav Biswas, Sergio Casas, Quinlan Sykora, Ben Agro, Abbas Sadat, Raquel Urtasun:
QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving. CoRR abs/2404.01486 (2024)
2023
[i152]
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Chris Zhang, Runsheng Guo, Wenyuan Zeng, Yuwen Xiong, Binbin Dai, Rui Hu, Mengye Ren, Raquel Urtasun:
Rethinking Closed-loop Training for Autonomous Driving. CoRR abs/2306.15713 (2023)
[i151]
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  - journals/corr/abs-2308-01471
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Ben Agro, Quinlan Sykora, Sergio Casas, Raquel Urtasun:
Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving. CoRR abs/2308.01471 (2023)
[i150]
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  - journals/corr/abs-2308-01898
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Ze Yang, Yun Chen, Jingkang Wang, Sivabalan Manivasagam, Wei-Chiu Ma, Anqi Joyce Yang, Raquel Urtasun:
UniSim: A Neural Closed-Loop Sensor Simulator. CoRR abs/2308.01898 (2023)
[i149]
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  - journals/corr/abs-2311-01017
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Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, Raquel Urtasun:
Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion. CoRR abs/2311.01017 (2023)
[i148]
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  - journals/corr/abs-2311-01394
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Chris Zhang, James Tu, Lunjun Zhang, Kelvin Wong, Simon Suo, Raquel Urtasun:
Learning Realistic Traffic Agents in Closed-loop. CoRR abs/2311.01394 (2023)
[i147]
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  - journals/corr/abs-2311-01444
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Anqi Joyce Yang, Sergio Casas, Nikita Dvornik, Sean Segal, Yuwen Xiong, Jordan Sir Kwang Hu, Carter Fang, Raquel Urtasun:
LabelFormer: Object Trajectory Refinement for Offboard Perception from LiDAR Point Clouds. CoRR abs/2311.01444 (2023)
[i146]
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  - journals/corr/abs-2311-01446
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Jay Sarva, Jingkang Wang, James Tu, Yuwen Xiong, Sivabalan Manivasagam, Raquel Urtasun:
Adv3D: Generating Safety-Critical 3D Objects through Closed-Loop Simulation. CoRR abs/2311.01446 (2023)
[i145]
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Jingkang Wang, Sivabalan Manivasagam, Yun Chen, Ze Yang, Ioan Andrei Bârsan, Anqi Joyce Yang, Wei-Chiu Ma, Raquel Urtasun:
CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation. CoRR abs/2311.01447 (2023)
[i144]
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  - journals/corr/abs-2311-01448
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Yuwen Xiong, Wei-Chiu Ma, Jingkang Wang, Raquel Urtasun:
UltraLiDAR: Learning Compact Representations for LiDAR Completion and Generation. CoRR abs/2311.01448 (2023)
[i143]
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  - journals/corr/abs-2311-01520
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Ali Athar, Enxu Li, Sergio Casas, Raquel Urtasun:
4D-Former: Multimodal 4D Panoptic Segmentation. CoRR abs/2311.01520 (2023)
[i142]
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  - journals/corr/abs-2311-01556
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Enxu Li, Sergio Casas, Raquel Urtasun:
MemorySeg: Online LiDAR Semantic Segmentation with a Latent Memory. CoRR abs/2311.01556 (2023)
[i141]
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  - journals/corr/abs-2311-02007
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Lunjun Zhang, Anqi Joyce Yang, Yuwen Xiong, Sergio Casas, Bin Yang, Mengye Ren, Raquel Urtasun:
Towards Unsupervised Object Detection From LiDAR Point Clouds. CoRR abs/2311.02007 (2023)
[i140]
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  - journals/corr/abs-2311-05602
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Ze Yang, Sivabalan Manivasagam, Yun Chen, Jingkang Wang, Rui Hu, Raquel Urtasun:
Reconstructing Objects in-the-wild for Realistic Sensor Simulation. CoRR abs/2311.05602 (2023)
[i139]
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  - journals/corr/abs-2311-05607
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Jeffrey Yunfan Liu, Yun Chen, Ze Yang, Jingkang Wang, Sivabalan Manivasagam, Raquel Urtasun:
Real-Time Neural Rasterization for Large Scenes. CoRR abs/2311.05607 (2023)
[i138]
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  - journals/corr/abs-2312-06654
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Ava Pun, Gary Sun, Jingkang Wang, Yun Chen, Ze Yang, Sivabalan Manivasagam, Wei-Chiu Ma, Raquel Urtasun:
LightSim: Neural Lighting Simulation for Urban Scenes. CoRR abs/2312.06654 (2023)
2022
[i137]
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  - journals/corr/abs-2206-08365
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Wei-Chiu Ma, Anqi Joyce Yang, Shenlong Wang, Raquel Urtasun, Antonio Torralba:
Virtual Correspondence: Humans as a Cue for Extreme-View Geometry. CoRR abs/2206.08365 (2022)
[i136]
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  - journals/corr/abs-2211-02545
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Alexander Cui, Sergio Casas, Kelvin Wong, Simon Suo, Raquel Urtasun:
GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting. CoRR abs/2211.02545 (2022)
2021
[i135]
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Katie Luo, Sergio Casas, Renjie Liao, Xinchen Yan, Yuwen Xiong, Wenyuan Zeng, Raquel Urtasun:
Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting. CoRR abs/2101.02385 (2021)
[i134]
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  - journals/corr/abs-2101-06541
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Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
SceneGen: Learning to Generate Realistic Traffic Scenes. CoRR abs/2101.06541 (2021)
[i133]
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  - journals/corr/abs-2101-06543
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Yun Chen, Frieda Rong, Shivam Duggal, Shenlong Wang, Xinchen Yan, Sivabalan Manivasagam, Shangjie Xue, Ersin Yumer, Raquel Urtasun:
GeoSim: Photorealistic Image Simulation with Geometry-Aware Composition. CoRR abs/2101.06543 (2021)
[i132]
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Namdar Homayounfar, Justin Liang, Wei-Chiu Ma, Raquel Urtasun:
VideoClick: Video Object Segmentation with a Single Click. CoRR abs/2101.06545 (2021)
[i131]
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Alexander Cui, Abbas Sadat, Sergio Casas, Renjie Liao, Raquel Urtasun:
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving. CoRR abs/2101.06547 (2021)
[i130]
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Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun:
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles. CoRR abs/2101.06549 (2021)
[i129]
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Yuwen Xiong, Mengye Ren, Wenyuan Zeng, Raquel Urtasun:
Self-Supervised Representation Learning from Flow Equivariance. CoRR abs/2101.06553 (2021)
[i128]
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Abbas Sadat, Sean Segal, Sergio Casas, James Tu, Bin Yang, Raquel Urtasun, Ersin Yumer:
Diverse Complexity Measures for Dataset Curation in Self-driving. CoRR abs/2101.06554 (2021)
[i127]
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Simon Suo, Sebastian Regalado, Sergio Casas, Raquel Urtasun:
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors. CoRR abs/2101.06557 (2021)
[i126]
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James Tu, Tsun-Hsuan Wang, Jingkang Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
Adversarial Attacks On Multi-Agent Communication. CoRR abs/2101.06560 (2021)
[i125]
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Anqi Joyce Yang, Can Cui, Ioan Andrei Bârsan, Raquel Urtasun, Shenlong Wang:
Asynchronous Multi-View SLAM. CoRR abs/2101.06562 (2021)
[i124]
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Ze Yang, Shenlong Wang, Sivabalan Manivasagam, Zeng Huang, Wei-Chiu Ma, Xinchen Yan, Ersin Yumer, Raquel Urtasun:
S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling. CoRR abs/2101.06571 (2021)
[i123]
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Bin Yang, Min Bai, Ming Liang, Wenyuan Zeng, Raquel Urtasun:
Auto4D: Learning to Label 4D Objects from Sequential Point Clouds. CoRR abs/2101.06586 (2021)
[i122]
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Jingkang Wang, Mengye Ren, Ilija Bogunovic, Yuwen Xiong, Raquel Urtasun:
Cost-Efficient Online Hyperparameter Optimization. CoRR abs/2101.06590 (2021)
[i121]
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Yan Wang, Bin Yang, Rui Hu, Ming Liang, Raquel Urtasun:
PLUME: Efficient 3D Object Detection from Stereo Images. CoRR abs/2101.06594 (2021)
[i120]
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Wenyuan Zeng, Yuwen Xiong, Raquel Urtasun:
Network Automatic Pruning: Start NAP and Take a Nap. CoRR abs/2101.06608 (2021)
[i119]
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Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun:
LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting. CoRR abs/2101.06653 (2021)
[i118]
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Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun:
End-to-end Interpretable Neural Motion Planner. CoRR abs/2101.06679 (2021)
[i117]
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John Phillips, Julieta Martinez, Ioan Andrei Bârsan, Sergio Casas, Abbas Sadat, Raquel Urtasun:
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction. CoRR abs/2101.06720 (2021)
[i116]
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Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, Raquel Urtasun:
Deep Parametric Continuous Convolutional Neural Networks. CoRR abs/2101.06742 (2021)
[i115]
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James Tu, Huichen Li, Xinchen Yan, Mengye Ren, Yun Chen, Ming Liang, Eilyan Bitar, Ersin Yumer, Raquel Urtasun:
Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving. CoRR abs/2101.06784 (2021)
[i114]
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Sergio Casas, Abbas Sadat, Raquel Urtasun:
MP3: A Unified Model to Map, Perceive, Predict and Plan. CoRR abs/2101.06806 (2021)
[i113]
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Jerry Liu, Wenyuan Zeng, Raquel Urtasun, Ersin Yumer:
Deep Structured Reactive Planning. CoRR abs/2101.06832 (2021)
[i112]
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Shivam Duggal, Zihao Wang, Wei-Chiu Ma, Sivabalan Manivasagam, Justin Liang, Shenlong Wang, Raquel Urtasun:
Secrets of 3D Implicit Object Shape Reconstruction in the Wild. CoRR abs/2101.06860 (2021)
[i111]
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Min Bai, Shenlong Wang, Kelvin Wong, Ersin Yumer, Raquel Urtasun:
Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving. CoRR abs/2101.06865 (2021)
[i110]
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  - journals/corr/abs-2101-07719
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Wei-Chiu Ma, Shenlong Wang, Jiayuan Gu, Sivabalan Manivasagam, Antonio Torralba, Raquel Urtasun:
Deep Feedback Inverse Problem Solver. CoRR abs/2101.07719 (2021)
[i109]
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Sergio Casas, Wenjie Luo, Raquel Urtasun:
IntentNet: Learning to Predict Intention from Raw Sensor Data. CoRR abs/2101.07907 (2021)
[i108]
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  - journals/corr/abs-2104-03956
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Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun:
Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes. CoRR abs/2104.03956 (2021)
[i107]
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  - journals/corr/abs-2106-13435
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Xiaohui Zeng, Raquel Urtasun, Richard S. Zemel, Sanja Fidler, Renjie Liao:
NP-DRAW: A Non-Parametric Structured Latent Variable Modelfor Image Generation. CoRR abs/2106.13435 (2021)
2020
[i106]
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  - journals/corr/abs-2004-00543
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James Tu, Mengye Ren, Siva Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun:
Physically Realizable Adversarial Examples for LiDAR Object Detection. CoRR abs/2004.00543 (2020)
[i105]
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  - journals/corr/abs-2005-07178
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Lila Huang, Shenlong Wang, Kelvin Wong, Jerry Liu, Raquel Urtasun:
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression. CoRR abs/2005.07178 (2020)
[i104]
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  - journals/corr/abs-2005-11626
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Kibok Lee, Zhuoyuan Chen, Xinchen Yan, Raquel Urtasun, Ersin Yumer:
ShapeAdv: Generating Shape-Aware Adversarial 3D Point Clouds. CoRR abs/2005.11626 (2020)
[i103]
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  - journals/corr/abs-2005-14711
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Ming Liang, Bin Yang, Wenyuan Zeng, Yun Chen, Rui Hu, Sergio Casas, Raquel Urtasun:
PnPNet: End-to-End Perception and Prediction with Tracking in the Loop. CoRR abs/2005.14711 (2020)
[i102]
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  - journals/corr/abs-2006-02636
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Sergio Casas, Cole Gulino, Simon Suo, Raquel Urtasun:
The Importance of Prior Knowledge in Precise Multimodal Prediction. CoRR abs/2006.02636 (2020)
[i101]
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  - journals/corr/abs-2006-09348
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Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Shuhan Tan, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World. CoRR abs/2006.09348 (2020)
[i100]
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  - journals/corr/abs-2007-05096
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Quinlan Sykora, Mengye Ren, Raquel Urtasun:
Multi-Agent Routing Value Iteration Network. CoRR abs/2007.05096 (2020)
[i99]
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  - journals/corr/abs-2007-11826
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Cong Han Lim, Raquel Urtasun, Ersin Yumer:
Hierarchical Verification for Adversarial Robustness. CoRR abs/2007.11826 (2020)
[i98]
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Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun:
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting. CoRR abs/2007.12036 (2020)
[i97]
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  - journals/corr/abs-2007-13732
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Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun:
Learning Lane Graph Representations for Motion Forecasting. CoRR abs/2007.13732 (2020)
[i96]
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  - journals/corr/abs-2007-14366
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Bin Yang, Runsheng Guo, Ming Liang, Sergio Casas, Raquel Urtasun:
RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects. CoRR abs/2007.14366 (2020)
[i95]
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  - journals/corr/abs-2007-15629
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Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun:
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation. CoRR abs/2007.15629 (2020)
[i94]
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  - journals/corr/abs-2008-01342
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Yuwen Xiong, Mengye Ren, Raquel Urtasun:
LoCo: Local Contrastive Representation Learning. CoRR abs/2008.01342 (2020)
[i93]
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  - journals/corr/abs-2008-05927
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Lingyun Luke Li, Bin Yang, Ming Liang, Wenyuan Zeng, Mengye Ren, Sean Segal, Raquel Urtasun:
End-to-end Contextual Perception and Prediction with Interaction Transformer. CoRR abs/2008.05927 (2020)
[i92]
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Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, Raquel Urtasun:
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations. CoRR abs/2008.05930 (2020)
[i91]
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Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun:
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction. CoRR abs/2008.06020 (2020)
[i90]
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  - journals/corr/abs-2008-06041
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Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun:
DSDNet: Deep Structured self-Driving Network. CoRR abs/2008.06041 (2020)
[i89]
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  - journals/corr/abs-2008-07519
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Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wenyuan Zeng, James Tu, Raquel Urtasun:
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction. CoRR abs/2008.07519 (2020)
[i88]
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  - journals/corr/abs-2008-09110
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Jiayuan Gu, Wei-Chiu Ma, Sivabalan Manivasagam, Wenyuan Zeng, Zihao Wang, Yuwen Xiong, Hao Su, Raquel Urtasun:
Weakly-supervised 3D Shape Completion in the Wild. CoRR abs/2008.09110 (2020)
[i87]
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  - journals/corr/abs-2008-09180
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Jerry Liu, Shenlong Wang, Wei-Chiu Ma, Meet Shah, Rui Hu, Pranaab Dhawan, Raquel Urtasun:
Conditional Entropy Coding for Efficient Video Compression. CoRR abs/2008.09180 (2020)
[i86]
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  - journals/corr/abs-2010-00731
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Meet Shah, Zhiling Huang, Ankit Laddha, Matthew Langford, Blake Barber, Sidney Zhang, Carlos Vallespi-Gonzalez, Raquel Urtasun:
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion. CoRR abs/2010.00731 (2020)
[i85]
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  - journals/corr/abs-2010-15703
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Julieta Martinez, Jashan Shewakramani, Ting-Wei Liu, Ioan Andrei Bârsan, Wenyuan Zeng, Raquel Urtasun:
Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks. CoRR abs/2010.15703 (2020)
[i84]
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  - journals/corr/abs-2011-01153
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Bob Wei, Mengye Ren, Wenyuan Zeng, Ming Liang, Bin Yang, Raquel Urtasun:
Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving. CoRR abs/2011.01153 (2020)
[i83]
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  - journals/corr/abs-2011-05289
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Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun:
Learning to Communicate and Correct Pose Errors. CoRR abs/2011.05289 (2020)
[i82]
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  - journals/corr/abs-2011-06165
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Sean Segal, Eric Kee, Wenjie Luo, Abbas Sadat, Ersin Yumer, Raquel Urtasun:
Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs. CoRR abs/2011.06165 (2020)
[i81]
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  - journals/corr/abs-2011-06425
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Davi Frossard, Simon Suo, Sergio Casas, James Tu, Rui Hu, Raquel Urtasun:
StrObe: Streaming Object Detection from LiDAR Packets. CoRR abs/2011.06425 (2020)
[i80]
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Sourav Biswas, Jerry Liu, Kelvin Wong, Shenlong Wang, Raquel Urtasun:
MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models. CoRR abs/2011.07590 (2020)
[i79]
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  - journals/corr/abs-2011-08106
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Ze Yang, Siva Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
Recovering and Simulating Pedestrians in the Wild. CoRR abs/2011.08106 (2020)
[i78]
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  - journals/corr/abs-2012-06980
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Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia:
GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation. CoRR abs/2012.06980 (2020)
[i77]
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Renjie Liao, Raquel Urtasun, Richard S. Zemel:
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks. CoRR abs/2012.07690 (2020)
[i76]
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  - journals/corr/abs-2012-10902
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Ioan Andrei Bârsan, Shenlong Wang, Andrei Pokrovsky, Raquel Urtasun:
Learning to Localize Using a LiDAR Intensity Map. CoRR abs/2012.10902 (2020)
[i75]
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  - journals/corr/abs-2012-10942
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Xinkai Wei, Ioan Andrei Bârsan, Shenlong Wang, Julieta Martinez, Raquel Urtasun:
Learning to Localize Through Compressed Binary Maps. CoRR abs/2012.10942 (2020)
[i74]
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  - journals/corr/abs-2012-10992
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Ming Liang, Bin Yang, Shenlong Wang, Raquel Urtasun:
Deep Continuous Fusion for Multi-Sensor 3D Object Detection. CoRR abs/2012.10992 (2020)
[i73]
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  - journals/corr/abs-2012-11585
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Justin Liang, Raquel Urtasun:
End-to-End Deep Structured Models for Drawing Crosswalks. CoRR abs/2012.11585 (2020)
[i72]
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  - journals/corr/abs-2012-11704
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Bin Yang, Ming Liang, Raquel Urtasun:
HDNET: Exploiting HD Maps for 3D Object Detection. CoRR abs/2012.11704 (2020)
[i71]
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  - journals/corr/abs-2012-12160
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Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Shenlong Wang, Raquel Urtasun:
Convolutional Recurrent Network for Road Boundary Extraction. CoRR abs/2012.12160 (2020)
[i70]
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  - journals/corr/abs-2012-12314
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Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun:
Hierarchical Recurrent Attention Networks for Structured Online Maps. CoRR abs/2012.12314 (2020)
[i69]
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  - journals/corr/abs-2012-12377
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Namdar Homayounfar, Wei-Chiu Ma, Justin Liang, Xinyu Wu, Jack Fan, Raquel Urtasun:
DAGMapper: Learning to Map by Discovering Lane Topology. CoRR abs/2012.12377 (2020)
[i68]
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  - journals/corr/abs-2012-12395
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Wenjie Luo, Bin Yang, Raquel Urtasun:
Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net. CoRR abs/2012.12395 (2020)
[i67]
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  - journals/corr/abs-2012-12397
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Ming Liang, Bin Yang, Yun Chen, Rui Hu, Raquel Urtasun:
Multi-Task Multi-Sensor Fusion for 3D Object Detection. CoRR abs/2012.12397 (2020)
[i66]
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  - journals/corr/abs-2012-12402
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Yun Chen, Bin Yang, Ming Liang, Raquel Urtasun:
Learning Joint 2D-3D Representations for Depth Completion. CoRR abs/2012.12402 (2020)
[i65]
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  - journals/corr/abs-2012-12437
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Julieta Martinez, Sasha Doubov, Jack Fan, Ioan Andrei Bârsan, Shenlong Wang, Gellért Máttyus, Raquel Urtasun:
Pit30M: A Benchmark for Global Localization in the Age of Self-Driving Cars. CoRR abs/2012.12437 (2020)
2019
[i64]
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  - journals/corr/abs-1901-01484
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Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel:
LanczosNet: Multi-Scale Deep Graph Convolutional Networks. CoRR abs/1901.01484 (2019)
[i63]
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  - journals/corr/abs-1901-03784
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Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun:
UPSNet: A Unified Panoptic Segmentation Network. CoRR abs/1901.03784 (2019)
[i62]
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  - journals/corr/abs-1902-06326
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Bin Yang, Wenjie Luo, Raquel Urtasun:
PIXOR: Real-time 3D Object Detection from Point Clouds. CoRR abs/1902.06326 (2019)
[i61]
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  - journals/corr/abs-1904-08913
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Wei-Chiu Ma, Shenlong Wang, Rui Hu, Yuwen Xiong, Raquel Urtasun:
Deep Rigid Instance Scene Flow. CoRR abs/1904.08913 (2019)
[i60]
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  - journals/corr/abs-1905-01333
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Davi Frossard, Eric Kee, Raquel Urtasun:
DeepSignals: Predicting Intent of Drivers Through Visual Signals. CoRR abs/1905.01333 (2019)
[i59]
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  - journals/corr/abs-1905-01555
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Min Bai, Gellért Máttyus, Namdar Homayounfar, Shenlong Wang, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun:
Deep Multi-Sensor Lane Detection. CoRR abs/1905.01555 (2019)
[i58]
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  - journals/corr/abs-1905-05889
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Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun:
DARNet: Deep Active Ray Network for Building Segmentation. CoRR abs/1905.05889 (2019)
[i57]
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  - journals/corr/abs-1907-13079
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Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong, Raquel Urtasun:
Deformable Filter Convolution for Point Cloud Reasoning. CoRR abs/1907.13079 (2019)
[i56]
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  - journals/corr/abs-1908-03274
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Wei-Chiu Ma, Ignacio Tartavull, Ioan Andrei Bârsan, Shenlong Wang, Min Bai, Gellért Máttyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky, Raquel Urtasun:
Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization. CoRR abs/1908.03274 (2019)
[i55]
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  - journals/corr/abs-1908-03631
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Jerry Liu, Shenlong Wang, Raquel Urtasun:
DSIC: Deep Stereo Image Compression. CoRR abs/1908.03631 (2019)
[i54]
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  - journals/corr/abs-1909-05845
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Shivam Duggal, Shenlong Wang, Wei-Chiu Ma, Rui Hu, Raquel Urtasun:
DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch. CoRR abs/1909.05845 (2019)
[i53]
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  - journals/corr/abs-1909-12471
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Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun:
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation. CoRR abs/1909.12471 (2019)
[i52]
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  - journals/corr/abs-1910-00760
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Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel:
Efficient Graph Generation with Graph Recurrent Attention Networks. CoRR abs/1910.00760 (2019)
[i51]
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  - journals/corr/abs-1910-04586
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Abbas Sadat, Mengye Ren, Andrei Pokrovsky, Yen-Chen Lin, Ersin Yumer, Raquel Urtasun:
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles. CoRR abs/1910.04586 (2019)
[i50]
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  - journals/corr/abs-1910-04650
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Yuwen Xiong, Mengye Ren, Raquel Urtasun:
Learning to Remember from a Multi-Task Teacher. CoRR abs/1910.04650 (2019)
[i49]
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  - journals/corr/abs-1910-08041
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Ajay Jain, Sergio Casas, Renjie Liao, Yuwen Xiong, Song Feng, Sean Segal, Raquel Urtasun:
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction. CoRR abs/1910.08041 (2019)
[i48]
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  - journals/corr/abs-1910-08233
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Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun:
Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data. CoRR abs/1910.08233 (2019)
[i47]
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  - journals/corr/abs-1910-11296
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Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun:
Identifying Unknown Instances for Autonomous Driving. CoRR abs/1910.11296 (2019)
[i46]
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  - journals/corr/abs-1912-02801
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Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Yuwen Xiong, Rui Hu, Raquel Urtasun:
PolyTransform: Deep Polygon Transformer for Instance Segmentation. CoRR abs/1912.02801 (2019)
[i45]
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  - journals/corr/abs-1912-11473
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Ze Yang, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Liwei Wang, Stephen Lin, Han Hu:
Dense RepPoints: Representing Visual Objects with Dense Point Sets. CoRR abs/1912.11473 (2019)
2018
[i44]
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  - journals/corr/abs-1801-02108
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Mengye Ren, Andrei Pokrovsky, Bin Yang, Raquel Urtasun:
SBNet: Sparse Blocks Network for Fast Inference. CoRR abs/1801.02108 (2018)
[i43]
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  - journals/corr/abs-1803-06272
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Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel:
Graph Partition Neural Networks for Semi-Supervised Classification. CoRR abs/1803.06272 (2018)
[i42]
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  - journals/corr/abs-1803-06329
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Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun:
Learning deep structured active contours end-to-end. CoRR abs/1803.06329 (2018)
[i41]
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  - journals/corr/abs-1803-06396
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Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel:
Reviving and Improving Recurrent Back-Propagation. CoRR abs/1803.06396 (2018)
[i40]
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  - journals/corr/abs-1803-07710
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KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow:
Inference in Probabilistic Graphical Models by Graph Neural Networks. CoRR abs/1803.07710 (2018)
[i39]
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  - journals/corr/abs-1803-09050
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Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun:
Learning to Reweight Examples for Robust Deep Learning. CoRR abs/1803.09050 (2018)
[i38]
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  - journals/corr/abs-1806-11534
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Davi Frossard, Raquel Urtasun:
End-to-end Learning of Multi-sensor 3D Tracking by Detection. CoRR abs/1806.11534 (2018)
[i37]
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  - journals/corr/abs-1809-02840
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Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel:
Neural Guided Constraint Logic Programming for Program Synthesis. CoRR abs/1809.02840 (2018)
[i36]
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  - journals/corr/abs-1810-05749
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Chris Zhang, Mengye Ren, Raquel Urtasun:
Graph HyperNetworks for Neural Architecture Search. CoRR abs/1810.05749 (2018)
[i35]
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  - journals/corr/abs-1812-01519
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Hang Chu, Wei-Chiu Ma, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
SurfConv: Bridging 3D and 2D Convolution for RGBD Images. CoRR abs/1812.01519 (2018)
2017
[i34]
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  - journals/corr/LuoLUZ17
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Wenjie Luo, Yujia Li, Raquel Urtasun, Richard S. Zemel:
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks. CoRR abs/1701.04128 (2017)
[i33]
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  - journals/corr/DaiLUF17
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Bo Dai, Dahua Lin, Raquel Urtasun, Sanja Fidler:
Towards Diverse and Natural Image Descriptions via a Conditional GAN. CoRR abs/1703.06029 (2017)
[i32]
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  - journals/corr/CastrejonKUF17
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Lluís Castrejón, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
Annotating Object Instances with a Polygon-RNN. CoRR abs/1704.05548 (2017)
[i31]
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Eleni Triantafillou, Richard S. Zemel, Raquel Urtasun:
Few-Shot Learning Through an Information Retrieval Lens. CoRR abs/1707.02610 (2017)
[i30]
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Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse:
The Reversible Residual Network: Backpropagation Without Storing Activations. CoRR abs/1707.04585 (2017)
[i29]
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  - journals/corr/abs-1708-04320
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Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler:
Situation Recognition with Graph Neural Networks. CoRR abs/1708.04320 (2017)
[i28]
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  - journals/corr/abs-1710-07346
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Shizhan Zhu, Sanja Fidler, Raquel Urtasun, Dahua Lin, Chen Change Loy:
Be Your Own Prada: Fashion Synthesis with Structural Coherence. CoRR abs/1710.07346 (2017)
2016
[i27]
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  - journals/corr/BaiLKU16
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Min Bai, Wenjie Luo, Kaustav Kundu, Raquel Urtasun:
Deep Semantic Matching for Optical Flow. CoRR abs/1604.01827 (2016)
[i26]
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  - journals/corr/HomayounfarFU16
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Namdar Homayounfar, Sanja Fidler, Raquel Urtasun:
Soccer Field Localization from a Single Image. CoRR abs/1604.02715 (2016)
[i25]
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Wei-Chiu Ma, Shenlong Wang, Marcus A. Brubaker, Sanja Fidler, Raquel Urtasun:
Find your Way by Observing the Sun and Other Semantic Cues. CoRR abs/1606.07415 (2016)
[i24]
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Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Huimin Ma, Sanja Fidler, Raquel Urtasun:
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection. CoRR abs/1608.07711 (2016)
[i23]
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  - journals/corr/ZengLFU16
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Wenyuan Zeng, Wenjie Luo, Sanja Fidler, Raquel Urtasun:
Efficient Summarization with Read-Again and Copy Mechanism. CoRR abs/1611.03382 (2016)
[i22]
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Hang Chu, Raquel Urtasun, Sanja Fidler:
Song From PI: A Musically Plausible Network for Pop Music Generation. CoRR abs/1611.03477 (2016)
[i21]
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Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel:
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. CoRR abs/1611.04520 (2016)
[i20]
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Min Bai, Raquel Urtasun:
Deep Watershed Transform for Instance Segmentation. CoRR abs/1611.08303 (2016)
[i19]
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Shenlong Wang, Min Bai, Gellért Máttyus, Hang Chu, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun:
TorontoCity: Seeing the World with a Million Eyes. CoRR abs/1612.00423 (2016)
[i18]
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Marvin Teichmann, Michael Weber, J. Marius Zöllner, Roberto Cipolla, Raquel Urtasun:
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving. CoRR abs/1612.07695 (2016)
2015
[i17]
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Yukun Zhu, Raquel Urtasun, Ruslan Salakhutdinov, Sanja Fidler:
segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection. CoRR abs/1502.04275 (2015)
[i16]
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Dahua Lin, Chen Kong, Sanja Fidler, Raquel Urtasun:
Generating Multi-Sentence Lingual Descriptions of Indoor Scenes. CoRR abs/1503.00064 (2015)
[i15]
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Alexander G. Schwing, Raquel Urtasun:
Fully Connected Deep Structured Networks. CoRR abs/1503.02351 (2015)
[i14]
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Ziyu Zhang, Alexander G. Schwing, Sanja Fidler, Raquel Urtasun:
Monocular Object Instance Segmentation and Depth Ordering with CNNs. CoRR abs/1505.03159 (2015)
[i13]
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Yukun Zhu, Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books. CoRR abs/1506.06724 (2015)
[i12]
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Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Antonio Torralba, Raquel Urtasun, Sanja Fidler:
Skip-Thought Vectors. CoRR abs/1506.06726 (2015)
[i11]
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Patrick Judd, Jorge Albericio, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger, Raquel Urtasun, Andreas Moshovos:
Reduced-Precision Strategies for Bounded Memory in Deep Neural Nets. CoRR abs/1511.05236 (2015)
[i10]
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Yang Song, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun:
Direct Loss Minimization for Training Deep Neural Nets. CoRR abs/1511.06411 (2015)
[i9]
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Makarand Tapaswi, Yukun Zhu, Rainer Stiefelhagen, Antonio Torralba, Raquel Urtasun, Sanja Fidler:
MovieQA: Understanding Stories in Movies through Question-Answering. CoRR abs/1512.02902 (2015)
[i8]
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Ziyu Zhang, Sanja Fidler, Raquel Urtasun:
Instance-Level Segmentation with Deep Densely Connected MRFs. CoRR abs/1512.06735 (2015)
2014
[i7]
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Xianjie Chen, Roozbeh Mottaghi, Xiaobai Liu, Sanja Fidler, Raquel Urtasun, Alan L. Yuille:
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts. CoRR abs/1406.2031 (2014)
[i6]
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Roozbeh Mottaghi, Sanja Fidler, Alan L. Yuille, Raquel Urtasun, Devi Parikh:
Human-Machine CRFs for Identifying Bottlenecks in Holistic Scene Understanding. CoRR abs/1406.3906 (2014)
[i5]
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Philip Lenz, Andreas Geiger, Raquel Urtasun:
FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation. CoRR abs/1407.6251 (2014)
2012
[i4]
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  - journals/corr/abs-1204-1393
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Koichiro Yamaguchi, Tamir Hazan, David A. McAllester, Raquel Urtasun:
Continuous Markov Random Fields for Robust Stereo Estimation. CoRR abs/1204.1393 (2012)
[i3]
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  - journals/corr/abs-1206-3242
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C. Mario Christoudias, Raquel Urtasun, Trevor Darrell:
Multi-View Learning in the Presence of View Disagreement. CoRR abs/1206.3242 (2012)
[i2]
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  - journals/corr/abs-1210-2346
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Tamir Hazan, Raquel Urtasun:
Efficient Learning of Structured Predictors in General Graphical Models. CoRR abs/1210.2346 (2012)
2010
[i1]
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  - journals/corr/abs-1006-2899
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Tamir Hazan, Raquel Urtasun:
Approximated Structured Prediction for Learning Large Scale Graphical Models. CoRR abs/1006.2899 (2010)

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