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ORCIDCVPR 2019: Long Beach, CA, USA
- IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019. Computer Vision Foundation / IEEE 2019
- Hongyang Li, David Eigen, Samuel Dodge, Matthew Zeiler, Xiaogang Wang:
Finding Task-Relevant Features for Few-Shot Learning by Category Traversal. 1-10 - Jongmin Kim, Taesup Kim, Sungwoong Kim, Chang D. Yoo:
Edge-Labeling Graph Neural Network for Few-Shot Learning. 11-20 - Spyros Gidaris, Nikos Komodakis:
Generating Classification Weights With GNN Denoising Autoencoders for Few-Shot Learning. 21-30 - Chen Wang
, Jianfei Yang, Lihua Xie, Junsong Yuan:
Kervolutional Neural Networks. 31-40 - Matthias Hein, Maksym Andriushchenko, Julian Bitterwolf:
Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem. 41-50 - Yusuke Tsuzuku, Issei Sato:
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions. 51-60 - Siyuan Qiao, Zhe Lin, Jianming Zhang, Alan L. Yuille:
Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization. 61-71 - Wenzhao Zheng, Zhaodong Chen, Jiwen Lu, Jie Zhou:
Hardness-Aware Deep Metric Learning. 72-81 - Chenxi Liu, Liang-Chieh Chen, Florian Schroff, Hartwig Adam, Wei Hua, Alan L. Yuille, Li Fei-Fei:
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation. 82-92 - Donggeun Yoo, In So Kweon:
Learning Loss for Active Learning. 93-102 - Salman H. Khan, Munawar Hayat, Syed Waqas Zamir, Jianbing Shen, Ling Shao:
Striking the Right Balance With Uncertainty. 103-112 - Ekin D. Cubuk, Barret Zoph, Dandelion Mané, Vijay Vasudevan, Quoc V. Le:
AutoAugment: Learning Augmentation Strategies From Data. 113-123 - Huu M. Le, Thanh-Toan Do, Tuan Hoang, Ngai-Man Cheung:
SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration Without Correspondences. 124-133 - Thomas Schöps, Torsten Sattler, Marc Pollefeys:
BAD SLAM: Bundle Adjusted Direct RGB-D SLAM. 134-144 - Francesco Pittaluga, Sanjeev J. Koppal, Sing Bing Kang, Sudipta N. Sinha:
Revealing Scenes by Inverting Structure From Motion Reconstructions. 145-154 - Giljoo Nam, Chenglei Wu, Min H. Kim, Yaser Sheikh:
Strand-Accurate Multi-View Hair Capture. 155-164 - Jeong Joon Park, Peter Florence, Julian Straub, Richard A. Newcombe, Steven Lovegrove:
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation. 165-174 - Pratul P. Srinivasan, Richard Tucker, Jonathan T. Barron, Ravi Ramamoorthi, Ren Ng, Noah Snavely:
Pushing the Boundaries of View Extrapolation With Multiplane Images. 175-184 - Feihu Zhang, Victor Adrian Prisacariu, Ruigang Yang, Philip H. S. Torr:
GA-Net: Guided Aggregation Net for End-To-End Stereo Matching. 185-194 - Alessio Tonioni, Fabio Tosi, Matteo Poggi, Stefano Mattoccia, Luigi Di Stefano:
Real-Time Self-Adaptive Deep Stereo. 195-204 - Sunok Kim, Seungryong Kim, Dongbo Min, Kwanghoon Sohn:
LAF-Net: Locally Adaptive Fusion Networks for Stereo Confidence Estimation. 205-214 - Chen Zhao, Zhiguo Cao, Chi Li, Xin Li, Jiaqi Yang:
NM-Net: Mining Reliable Neighbors for Robust Feature Correspondences. 215-224 - Matthew Trager, Martial Hebert, Jean Ponce:
Coordinate-Free Carlsson-Weinshall Duality and Relative Multi-View Geometry. 225-233 - Xiaoguang Han, Zhaoxuan Zhang, Dong Du, Mingdai Yang, Jingming Yu, Pan Pan, Xin Yang, Ligang Liu, Zixiang Xiong, Shuguang Cui:
Deep Reinforcement Learning of Volume-Guided Progressive View Inpainting for 3D Point Scene Completion From a Single Depth Image. 234-243 - Rohit Girdhar, João Carreira, Carl Doersch, Andrew Zisserman:
Video Action Transformer Network. 244-253 - Noureldien Hussein, Efstratios Gavves, Arnold W. M. Smeulders:
Timeception for Complex Action Recognition. 254-263 - Xitong Yang, Xiaodong Yang, Ming-Yu Liu, Fanyi Xiao, Larry S. Davis, Jan Kautz:
STEP: Spatio-Temporal Progressive Learning for Video Action Detection. 264-272 - Chen Sun, Abhinav Shrivastava, Carl Vondrick, Rahul Sukthankar, Kevin Murphy, Cordelia Schmid:
Relational Action Forecasting. 273-283 - Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krähenbühl, Ross B. Girshick:
Long-Term Feature Banks for Detailed Video Understanding. 284-293 - Yuke Li:
Which Way Are You Going? Imitative Decision Learning for Path Forecasting in Dynamic Scenes. 294-303 - Paritosh Parmar, Brendan Tran Morris:
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment. 304-313 - Shuangjie Xu, Daizong Liu, Linchao Bao, Wei Liu, Pan Zhou:
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation. 314-323 - Ruohan Gao, Kristen Grauman:
2.5D Visual Sound. - Weining Wang, Yan Huang, Liang Wang:
Language-Driven Temporal Activity Localization: A Semantic Matching Reinforcement Learning Model. 334-343 - Fuchen Long, Ting Yao, Zhaofan Qiu, Xinmei Tian, Jiebo Luo, Tao Mei:
Gaussian Temporal Awareness Networks for Action Localization. 344-353 - Shweta Bhardwaj, Mukundhan Srinivasan, Mitesh M. Khapra:
Efficient Video Classification Using Fewer Frames. 354-363 - Lu Yang, Qing Song, Zhihui Wang, Ming Jiang:
Parsing R-CNN for Instance-Level Human Analysis. 364-373 - Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, Yun Fu:
Large Scale Incremental Learning. 374-382 - Lyne P. Tchapmi, Vineet Kosaraju, Hamid Rezatofighi, Ian D. Reid, Silvio Savarese:
TopNet: Structural Point Cloud Decoder. 383-392 - Yifan Sun, Qin Xu, Yali Li, Chi Zhang, Yikang Li, Shengjin Wang, Jian Sun:
Perceive Where to Focus: Learning Visibility-Aware Part-Level Features for Partial Person Re-Identification. 393-402 - Qianru Sun, Yaoyao Liu, Tat-Seng Chua, Bernt Schiele:
Meta-Transfer Learning for Few-Shot Learning. 403-412 - Bohan Zhuang, Chunhua Shen, Mingkui Tan, Lingqiao Liu, Ian D. Reid:
Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation. 413-422 - Bo Pang, Kaiwen Zha, Hanwen Cao, Chen Shi, Cewu Lu:
Deep RNN Framework for Visual Sequential Applications. 423-432 - Yunpeng Chen, Marcus Rohrbach, Zhicheng Yan, Shuicheng Yan, Jiashi Feng, Yannis Kalantidis:
Graph-Based Global Reasoning Networks. 433-442 - Wenqi Shao, Tianjian Meng, Jingyu Li, Ruimao Zhang, Yudian Li, Xiaogang Wang, Ping Luo:
SSN: Learning Sparse Switchable Normalization via SparsestMax. 443-451 - Yongming Rao, Jiwen Lu, Jie Zhou:
Spherical Fractal Convolutional Neural Networks for Point Cloud Recognition. 452-460 - Shashank Tripathi, Siddhartha Chandra, Amit Agrawal, Ambrish Tyagi, James M. Rehg, Visesh Chari:
Learning to Generate Synthetic Data via Compositing. 461-470 - Artsiom Sanakoyeu, Vadim Tschernezki, Uta Büchler, Björn Ommer:
Divide and Conquer the Embedding Space for Metric Learning. 471-480 - Davide Abati, Angelo Porrello, Simone Calderara, Rita Cucchiara:
Latent Space Autoregression for Novelty Detection. 481-490 - Vinod Kumar Kurmi, Shanu Kumar, Vinay P. Namboodiri:
Attending to Discriminative Certainty for Domain Adaptation. 491-500 - Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan L. Yuille, Kaiming He:
Feature Denoising for Improving Adversarial Robustness. 501-509 - Xiang Li, Wenhai Wang, Xiaolin Hu, Jian Yang:
Selective Kernel Networks. 510-519 - Dushyant Mehta, Kwang In Kim, Christian Theobalt:
On Implicit Filter Level Sparsity in Convolutional Neural Networks. 520-528 - Xingyu Liu, Charles R. Qi, Leonidas J. Guibas:
FlowNet3D: Learning Scene Flow in 3D Point Clouds. 529-537 - Kuan Fang, Alexander Toshev, Li Fei-Fei, Silvio Savarese:
Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks. 538-547 - Hang Zhang, Han Zhang, Chenguang Wang, Junyuan Xie:
Co-Occurrent Features in Semantic Segmentation. 548-557 - Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li:
Bag of Tricks for Image Classification with Convolutional Neural Networks. 558-567 - Ziwei Wang, Jiwen Lu, Chenxin Tao, Jie Zhou, Qi Tian:
Learning Channel-Wise Interactions for Binary Convolutional Neural Networks. 568-577 - Tong He, Chunhua Shen, Zhi Tian, Dong Gong, Changming Sun, Youliang Yan:
Knowledge Adaptation for Efficient Semantic Segmentation. 578-587 - Zhezhi He, Adnan Siraj Rakin, Deliang Fan:
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack. 588-597 - Zhun Zhong, Liang Zheng, Zhiming Luo, Shaozi Li, Yi Yang:
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-Identification. 598-607 - Xiaoxiao Sun, Liang Zheng:
Dissecting Person Re-Identification From the Viewpoint of Viewpoint. 608-617 - Zhixiang Wang, Zheng Wang, Yinqiang Zheng, Yung-Yu Chuang, Shin'ichi Satoh:
Learning to Reduce Dual-Level Discrepancy for Infrared-Visible Person Re-Identification. 618-626 - Chaoqi Chen, Weiping Xie, Wenbing Huang, Yu Rong, Xinghao Ding, Yue Huang, Tingyang Xu, Junzhou Huang:
Progressive Feature Alignment for Unsupervised Domain Adaptation. 627-636 - Xiaofeng Liu, Site Li, Lingsheng Kong, Wanqing Xie, Ping Jia, Jane You, B. V. K. Vijaya Kumar:
Feature-Level Frankenstein: Eliminating Variations for Discriminative Recognition. 637-646 - Thibaut Durand, Nazanin Mehrasa, Greg Mori:
Learning a Deep ConvNet for Multi-Label Classification With Partial Labels. 647-657 - Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak, Amir Sadeghian, Ian D. Reid, Silvio Savarese:
Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression. 658-666 - Zhizheng Zhang, Cuiling Lan, Wenjun Zeng, Zhibo Chen:
Densely Semantically Aligned Person Re-Identification. 667-676 - Kaiyue Pang, Ke Li, Yongxin Yang, Honggang Zhang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Generalising Fine-Grained Sketch-Based Image Retrieval. 677-686 - Xinge Zhu, Jiangmiao Pang, Ceyuan Yang, Jianping Shi, Dahua Lin:
Adapting Object Detectors via Selective Cross-Domain Alignment. 687-696 - Yunhang Shen, Rongrong Ji, Yan Wang, Yongjian Wu, Liujuan Cao:
Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation. 697-707 - Aron Yu, Kristen Grauman:
Thinking Outside the Pool: Active Training Image Creation for Relative Attributes. 708-718 - Jifei Song, Yongxin Yang, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Generalizable Person Re-Identification by Domain-Invariant Mapping Network. 719-728 - Hao Guo, Kang Zheng, Xiaochuan Fan, Hongkai Yu, Song Wang:
Visual Attention Consistency Under Image Transforms for Multi-Label Image Classification. 729-739 - Song Bai, Peng Tang, Philip H. S. Torr, Longin Jan Latecki:
Re-Ranking via Metric Fusion for Object Retrieval and Person Re-Identification. 740-749 - Junbao Zhuo, Shuhui Wang, Shuhao Cui, Qingming Huang:
Unsupervised Open Domain Recognition by Semantic Discrepancy Minimization. 750-759 - Jingke Meng, Sheng Wu, Wei-Shi Zheng:
Weakly Supervised Person Re-Identification. 760-769 - Shaoshuai Shi, Xiaogang Wang, Hongsheng Li:
PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud. 770-779 - Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik G. Learned-Miller:
Automatic Adaptation of Object Detectors to New Domains Using Self-Training. 780-790 - Jiaxin Chen, Jie Qin, Li Liu, Fan Zhu, Fumin Shen, Jin Xie, Ling Shao:
Deep Sketch-Shape Hashing With Segmented 3D Stochastic Viewing. 791-800 - He Huang, Changhu Wang, Philip S. Yu, Chang-Dong Wang:
Generative Dual Adversarial Network for Generalized Zero-Shot Learning. 801-810 - Bharti Munjal, Sikandar Amin, Federico Tombari, Fabio Galasso:
Query-Guided End-To-End Person Search. 811-820 - Jiangmiao Pang, Kai Chen, Jianping Shi, Huajun Feng, Wanli Ouyang, Dahua Lin:
Libra R-CNN: Towards Balanced Learning for Object Detection. 821-830 - Saihui Hou, Xinyu Pan, Chen Change Loy, Zilei Wang, Dahua Lin:
Learning a Unified Classifier Incrementally via Rebalancing. 831-839 - Chenchen Zhu, Yihui He, Marios Savvides:
Feature Selective Anchor-Free Module for Single-Shot Object Detection. 840-849 - Xingyi Zhou, Jiacheng Zhuo, Philipp Krähenbühl:
Bottom-Up Object Detection by Grouping Extreme and Center Points. 850-859 - Zihao Liu, Qi Liu, Tao Liu, Nuo Xu, Xue Lin, Yanzhi Wang, Wujie Wen:
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples. 860-868 - Wei-Chih Hung, Varun Jampani, Sifei Liu, Pavlo Molchanov, Ming-Hsuan Yang, Jan Kautz:
SCOPS: Self-Supervised Co-Part Segmentation. 869-878 - Yanchao Yang, Antonio Loquercio, Davide Scaramuzza, Stefano Soatto:
Unsupervised Moving Object Detection via Contextual Information Separation. 879-888 - Song-Hai Zhang, Ruilong Li, Xin Dong, Paul L. Rosin, Zixi Cai, Xi Han, Dingcheng Yang, Haozhi Huang, Shi-Min Hu:
Pose2Seg: Detection Free Human Instance Segmentation. 889-898 - Guorun Yang, Xiao Song, Chaoqin Huang, Zhidong Deng, Jianping Shi, Bolei Zhou:
DrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios. 899-908 - Kaichun Mo, Shilin Zhu, Angel X. Chang, Li Yi, Subarna Tripathi, Leonidas J. Guibas, Hao Su:
PartNet: A Large-Scale Benchmark for Fine-Grained and Hierarchical Part-Level 3D Object Understanding. 909-918 - Shifeng Zhang, Xiaobo Wang, Ajian Liu, Chenxu Zhao, Jun Wan, Sergio Escalera, Hailin Shi, Zezheng Wang, Stan Z. Li:
A Dataset and Benchmark for Large-Scale Multi-Modal Face Anti-Spoofing. 919-928 - Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Unsupervised Learning of Consensus Maximization for 3D Vision Problems. 929-938 - Danna Gurari, Qing Li, Chi Lin, Yinan Zhao, Anhong Guo, Abigale Stangl, Jeffrey P. Bigham:
VizWiz-Priv: A Dataset for Recognizing the Presence and Purpose of Private Visual Information in Images Taken by Blind People. 939-948 - Yueqi Duan, Yu Zheng, Jiwen Lu, Jie Zhou, Qi Tian:
Structural Relational Reasoning of Point Clouds. 949-958 - Fanzi Wu, Linchao Bao, Yajing Chen, Yonggen Ling, Yibing Song, Songnan Li, King Ngi Ngan, Wei Liu:
MVF-Net: Multi-View 3D Face Morphable Model Regression. 959-968 - Chen-Hsuan Lin, Oliver Wang, Bryan C. Russell, Eli Shechtman, Vladimir G. Kim, Matthew Fisher, Simon Lucey:
Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction. 969-978 - Matteo Poggi, Davide Pallotti, Fabio Tosi, Stefano Mattoccia:
Guided Stereo Matching. 979-988 - Alex Zihao Zhu, Liangzhe Yuan, Kenneth Chaney, Kostas Daniilidis:
Unsupervised Event-Based Learning of Optical Flow, Depth, and Egomotion. 989-997 - Shiyi Lan, Ruichi Yu, Gang Yu, Larry S. Davis:
Modeling Local Geometric Structure of 3D Point Clouds Using Geo-CNN. 998-1008 - Yongheng Zhao, Tolga Birdal, Haowen Deng, Federico Tombari:
3D Point Capsule Networks. 1009-1018 - Buyu Li, Wanli Ouyang, Lu Sheng, Xingyu Zeng, Xiaogang Wang:
GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving. 1019-1028 - Zehao Yu, Jia Zheng, Dongze Lian, Zihan Zhou, Shenghua Gao:
Single-Image Piece-Wise Planar 3D Reconstruction via Associative Embedding. 1029-1037 - Weiyue Wang, Duygu Ceylan, Radomír Mech, Ulrich Neumann:
3DN: 3D Deformation Network. 1038-1046 - Cheng Sun, Chi-Wei Hsiao, Min Sun, Hwann-Tzong Chen:
HorizonNet: Learning Room Layout With 1D Representation and Pano Stretch Data Augmentation. 1047-1056 - Lijie Liu, Jiwen Lu, Chunjing Xu, Qi Tian, Jie Zhou:
Deep Fitting Degree Scoring Network for Monocular 3D Object Detection. 1057-1066 - Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Pushing the Envelope for RGB-Based Dense 3D Hand Pose Estimation via Neural Rendering. 1067-1076