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2020 – today
- 2023
[c37]Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin:
Magic3D: High-Resolution Text-to-3D Content Creation. CVPR 2023: 300-309- [c36]Chenlin Meng, Jiaming Song, Shuang Li, Jun-Yan Zhu, Stefano Ermon, Tsung-Yi Lin, Chen-Hsuan Lin, Karsten Kreis:
SIGGRAPH 2023 Course on Diffusion Models. SIGGRAPH Courses 2023: 7:1-7:113 - [c35]Kai-En Lin, Yen-Chen Lin, Wei-Sheng Lai, Tsung-Yi Lin, Yi-Chang Shih, Ravi Ramamoorthi:
Vision Transformer for NeRF-Based View Synthesis from a Single Input Image. WACV 2023: 806-815 - [i38]Tsai-Shien Chen, Chieh Hubert Lin, Hung-Yu Tseng, Tsung-Yi Lin, Ming-Hsuan Yang:
Motion-Conditioned Diffusion Model for Controllable Video Synthesis. CoRR abs/2304.14404 (2023) - [i37]Jonathan Lorraine, Kevin Xie, Xiaohui Zeng, Chen-Hsuan Lin, Towaki Takikawa, Nicholas Sharp, Tsung-Yi Lin, Ming-Yu Liu, Sanja Fidler, James Lucas:
ATT3D: Amortized Text-to-3D Object Synthesis. CoRR abs/2306.07349 (2023) - 2022
- [j3]Dahun Kim
, Tsung-Yi Lin, Anelia Angelova, In So Kweon, Weicheng Kuo:
Learning Open-World Object Proposals Without Learning to Classify. IEEE Robotics Autom. Lett. 7(2): 5453-5460 (2022) - [c34]Boyi Li, Yin Cui, Tsung-Yi Lin, Serge J. Belongie:
SITTA: Single Image Texture Translation for Data Augmentation. ECCV Workshops (2) 2022: 3-20 - [c33]Golnaz Ghiasi, Xiuye Gu, Yin Cui, Tsung-Yi Lin:
Scaling Open-Vocabulary Image Segmentation with Image-Level Labels. ECCV (36) 2022: 540-557 - [c32]Wuyang Chen, Xianzhi Du, Fan Yang, Lucas Beyer, Xiaohua Zhai, Tsung-Yi Lin, Huizhong Chen, Jing Li, Xiaodan Song, Zhangyang Wang, Denny Zhou:
A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation. ECCV (10) 2022: 711-727 - [c31]Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, Yin Cui:
Open-vocabulary Object Detection via Vision and Language Knowledge Distillation. ICLR 2022 - [c30]Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Tsung-Yi Lin, Alberto Rodriguez, Phillip Isola:
NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields. ICRA 2022: 6496-6503 - [c29]Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey E. Hinton:
A Unified Sequence Interface for Vision Tasks. NeurIPS 2022 - [i36]Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Tsung-Yi Lin, Alberto Rodriguez Garcia, Phillip Isola:
NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields. CoRR abs/2203.01913 (2022) - [i35]Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey E. Hinton:
A Unified Sequence Interface for Vision Tasks. CoRR abs/2206.07669 (2022) - [i34]Kai-En Lin, Yen-Chen Lin, Wei-Sheng Lai, Tsung-Yi Lin, Yi-Chang Shih, Ravi Ramamoorthi:
Vision Transformer for NeRF-Based View Synthesis from a Single Input Image. CoRR abs/2207.05736 (2022) - [i33]Xianzhi Du, Wei-Chih Hung, Tsung-Yi Lin:
Optimizing Anchor-based Detectors for Autonomous Driving Scenes. CoRR abs/2208.06062 (2022) - [i32]Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin:
Magic3D: High-Resolution Text-to-3D Content Creation. CoRR abs/2211.10440 (2022) - 2021
- [c28]Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph:
Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation. CVPR 2021: 2918-2928 - [c27]Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani:
Bottleneck Transformers for Visual Recognition. CVPR 2021: 16519-16529 - [c26]Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin:
Multi-Task Self-Training for Learning General Representations. ICCV 2021: 8836-8845 - [c25]Weicheng Kuo, Anelia Angelova, Tsung-Yi Lin, Angela Dai:
Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Image. ICCV 2021: 12569-12579 - [c24]Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Alberto Rodriguez, Phillip Isola, Tsung-Yi Lin:
iNeRF: Inverting Neural Radiance Fields for Pose Estimation. IROS 2021: 1323-1330 - [c23]Irwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. NeurIPS 2021: 22614-22627 - [i31]Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani:
Bottleneck Transformers for Visual Recognition. CoRR abs/2101.11605 (2021) - [i30]Irwan Bello, William Fedus, Xianzhi Du, Ekin D. Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. CoRR abs/2103.07579 (2021) - [i29]Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, Yin Cui:
Zero-Shot Detection via Vision and Language Knowledge Distillation. CoRR abs/2104.13921 (2021) - [i28]Boyi Li, Yin Cui, Tsung-Yi Lin, Serge J. Belongie:
Single Image Texture Translation for Data Augmentation. CoRR abs/2106.13804 (2021) - [i27]Xianzhi Du, Barret Zoph, Wei-Chih Hung, Tsung-Yi Lin:
Simple Training Strategies and Model Scaling for Object Detection. CoRR abs/2107.00057 (2021) - [i26]Yen-Chen Lin, Andy Zeng, Shuran Song, Phillip Isola, Tsung-Yi Lin:
Learning to See before Learning to Act: Visual Pre-training for Manipulation. CoRR abs/2107.00646 (2021) - [i25]Dahun Kim, Tsung-Yi Lin, Anelia Angelova, In So Kweon, Weicheng Kuo:
Learning Open-World Object Proposals without Learning to Classify. CoRR abs/2108.06753 (2021) - [i24]Weicheng Kuo, Anelia Angelova, Tsung-Yi Lin, Angela Dai:
Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Image. CoRR abs/2108.09368 (2021) - [i23]Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin:
Multi-Task Self-Training for Learning General Representations. CoRR abs/2108.11353 (2021) - [i22]Wuyang Chen, Xianzhi Du, Fan Yang, Lucas Beyer, Xiaohua Zhai, Tsung-Yi Lin, Huizhong Chen, Jing Li, Xiaodan Song, Zhangyang Wang, Denny Zhou:
A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation. CoRR abs/2112.09747 (2021) - [i21]Golnaz Ghiasi, Xiuye Gu, Yin Cui, Tsung-Yi Lin:
Open-Vocabulary Image Segmentation. CoRR abs/2112.12143 (2021) - 2020
- [j2]Tsung-Yi Lin, Priya Goyal, Ross B. Girshick, Kaiming He, Piotr Dollár:
Focal Loss for Dense Object Detection. IEEE Trans. Pattern Anal. Mach. Intell. 42(2): 318-327 (2020) - [c22]Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V. Le, Xiaodan Song:
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization. CVPR 2020: 11589-11598 - [c21]Bo Chen, Golnaz Ghiasi, Hanxiao Liu, Tsung-Yi Lin, Dmitry Kalenichenko, Hartwig Adam, Quoc V. Le:
MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices. CVPR 2020: 13604-13613 - [c20]Weicheng Kuo, Anelia Angelova, Tsung-Yi Lin, Angela Dai:
Mask2CAD: 3D Shape Prediction by Learning to Segment and Retrieve. ECCV (3) 2020: 260-277 - [c19]Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le:
Learning Data Augmentation Strategies for Object Detection. ECCV (27) 2020: 566-583 - [c18]Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song:
Efficient Scale-Permuted Backbone with Learned Resource Distribution. ECCV (23) 2020: 572-586 - [c17]Yen-Chen Lin, Andy Zeng, Shuran Song, Phillip Isola, Tsung-Yi Lin:
Learning to See before Learning to Act: Visual Pre-training for Manipulation. ICRA 2020: 7286-7293 - [c16]Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin Dogus Cubuk, Quoc Le:
Rethinking Pre-training and Self-training. NeurIPS 2020 - [i20]Ankita Pasad, Ariel Gordon, Tsung-Yi Lin, Anelia Angelova:
Improving Semantic Segmentation through Spatio-Temporal Consistency Learned from Videos. CoRR abs/2004.05324 (2020) - [i19]Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin D. Cubuk, Quoc V. Le:
Rethinking Pre-training and Self-training. CoRR abs/2006.06882 (2020) - [i18]Weicheng Kuo, Anelia Angelova, Tsung-Yi Lin, Angela Dai:
Mask2CAD: 3D Shape Prediction by Learning to Segment and Retrieve. CoRR abs/2007.13034 (2020) - [i17]Wei-Chih Hung, Henrik Kretzschmar, Tsung-Yi Lin, Yuning Chai, Ruichi Yu, Ming-Hsuan Yang, Dragomir Anguelov:
SoDA: Multi-Object Tracking with Soft Data Association. CoRR abs/2008.07725 (2020) - [i16]Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song:
Efficient Scale-Permuted Backbone with Learned Resource Distribution. CoRR abs/2010.11426 (2020) - [i15]Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Alberto Rodriguez Garcia, Phillip Isola, Tsung-Yi Lin:
iNeRF: Inverting Neural Radiance Fields for Pose Estimation. CoRR abs/2012.05877 (2020) - [i14]Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph:
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation. CoRR abs/2012.07177 (2020)
2010 – 2019
- 2019
- [c15]Golnaz Ghiasi, Tsung-Yi Lin, Quoc V. Le:
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection. CVPR 2019: 7036-7045 - [c14]Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, Serge J. Belongie:
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019: 9268-9277 - [c13]Weicheng Kuo, Anelia Angelova, Jitendra Malik, Tsung-Yi Lin:
ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors. ICCV 2019: 9206-9215 - [i13]Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, Serge J. Belongie:
Class-Balanced Loss Based on Effective Number of Samples. CoRR abs/1901.05555 (2019) - [i12]Weicheng Kuo, Anelia Angelova, Jitendra Malik, Tsung-Yi Lin:
ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors. CoRR abs/1904.03239 (2019) - [i11]Golnaz Ghiasi, Tsung-Yi Lin, Ruoming Pang, Quoc V. Le:
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection. CoRR abs/1904.07392 (2019) - [i10]Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le:
Learning Data Augmentation Strategies for Object Detection. CoRR abs/1906.11172 (2019) - [i9]Bo Chen, Golnaz Ghiasi, Hanxiao Liu, Tsung-Yi Lin, Dmitry Kalenichenko, Hartwig Adam, Quoc V. Le:
MnasFPN: Learning Latency-aware Pyramid Architecture for Object Detection on Mobile Devices. CoRR abs/1912.01106 (2019) - [i8]Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V. Le, Xiaodan Song:
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization. CoRR abs/1912.05027 (2019) - 2018
- [c12]Golnaz Ghiasi, Tsung-Yi Lin, Quoc V. Le:
DropBlock: A regularization method for convolutional networks. NeurIPS 2018: 10750-10760 - [i7]Golnaz Ghiasi, Tsung-Yi Lin, Quoc V. Le:
DropBlock: A regularization method for convolutional networks. CoRR abs/1810.12890 (2018) - 2017
- [c11]Tsung-Yi Lin, Piotr Dollár, Ross B. Girshick, Kaiming He, Bharath Hariharan, Serge J. Belongie:
Feature Pyramid Networks for Object Detection. CVPR 2017: 936-944 - [c10]Tsung-Yi Lin, Priya Goyal, Ross B. Girshick, Kaiming He, Piotr Dollár:
Focal Loss for Dense Object Detection. ICCV 2017: 2999-3007 - [c9]Cheng-Kang Hsieh, Longqi Yang, Yin Cui, Tsung-Yi Lin, Serge J. Belongie, Deborah Estrin:
Collaborative Metric Learning. WWW 2017: 193-201 - [i6]Tsung-Yi Lin, Priya Goyal, Ross B. Girshick, Kaiming He, Piotr Dollár:
Focal Loss for Dense Object Detection. CoRR abs/1708.02002 (2017) - 2016
- [c8]Sergey Zagoruyko, Adam Lerer, Tsung-Yi Lin, Pedro Oliveira Pinheiro, Sam Gross, Soumith Chintala, Piotr Dollár:
A MultiPath Network for Object Detection. BMVC 2016 - [c7]Pedro Oliveira Pinheiro, Tsung-Yi Lin, Ronan Collobert, Piotr Dollár:
Learning to Refine Object Segments. ECCV (1) 2016: 75-91 - [p1]Tsung-Yi Lin, Serge J. Belongie, James Hays:
Cross-View Image Geo-localization. Large-Scale Visual Geo-Localization 2016: 59-76 - [i5]Pedro H. O. Pinheiro, Tsung-Yi Lin, Ronan Collobert, Piotr Dollár:
Learning to Refine Object Segments. CoRR abs/1603.08695 (2016) - [i4]Sergey Zagoruyko, Adam Lerer, Tsung-Yi Lin, Pedro H. O. Pinheiro, Sam Gross, Soumith Chintala, Piotr Dollár:
A MultiPath Network for Object Detection. CoRR abs/1604.02135 (2016) - [i3]Tsung-Yi Lin, Piotr Dollár, Ross B. Girshick, Kaiming He, Bharath Hariharan, Serge J. Belongie:
Feature Pyramid Networks for Object Detection. CoRR abs/1612.03144 (2016) - 2015
- [c6]Tsung-Yi Lin, Yin Cui, Serge J. Belongie, James Hays:
Learning deep representations for ground-to-aerial geolocalization. CVPR 2015: 5007-5015 - [i2]Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, C. Lawrence Zitnick:
Microsoft COCO Captions: Data Collection and Evaluation Server. CoRR abs/1504.00325 (2015) - 2014
- [j1]Nick C. Tang, Chiou-Ting Hsu, Ming-Fang Weng, Tsung-Yi Lin, Hong-Yuan Mark Liao:
Example-Based Human Motion Extrapolation and Motion Repairing Using Contour Manifold. IEEE Trans. Multim. 16(1): 47-59 (2014) - [c5]Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, C. Lawrence Zitnick:
Microsoft COCO: Common Objects in Context. ECCV (5) 2014: 740-755 - [i1]Tsung-Yi Lin, Michael Maire, Serge J. Belongie, Lubomir D. Bourdev, Ross B. Girshick, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, C. Lawrence Zitnick:
Microsoft COCO: Common Objects in Context. CoRR abs/1405.0312 (2014) - 2013
- [c4]Tsung-Yi Lin, Serge J. Belongie, James Hays:
Cross-View Image Geolocalization. CVPR 2013: 891-898 - 2011
- [c3]Nick C. Tang, Chiou-Ting Hsu, Tsung-Yi Lin, Hong-Yuan Mark Liao:
Example-based human motion extrapolation based on manifold learning. ACM Multimedia 2011: 1305-1308 - [c2]Tsung-Yi Lin, Yen-Yu Lin, Ming-Fang Weng, Yu-Chiang Frank Wang, Yu-Feng Hsu, Hong-Yuan Mark Liao:
Cross camera people counting with perspective estimation and occlusion handling. WIFS 2011: 1-6
2000 – 2009
- 2009
- [c1]Wen-Fu Lee, Tsung-Yi Lin, Mei-Lan Chu, Tai-Hsiang Huang, Homer H. Chen:
Perception-based high dynamic range compression in gradient domain. ICIP 2009: 1805-1808
Coauthor Index
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