Low-Level Vision
Let's enhance! Our team has been working on various image/video restoration and enhancement problems such as super-resolution, denoising, low-light enhancement etc. Some notable methods developed by us include SRCNN, ESRGAN, EDVR, BasicVSR, and Zero-DCE.
Super-Resolution
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Investigating Tradeoffs in Real-World Video Super-Resolution
K. C. K. Chan, S. Zhou, X. Xu, C. C. Loy
Technical report, arXiv:2111.12704, 2021
[arXiv] [Project Page] -
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment
K. C. K. Chan, S. Zhou, X. Xu, C. C. Loy
Technical report, arXiv:2104.13371, 2021
[arXiv] [Project Page] -
GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution
K. C. K. Chan, X. Wang, X. Xu, J. Gu, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR, Oral)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
K. C. K. Chan, X. Wang, K. Yu, C. Dong, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Robust Reference-based Super-Resolution via C2-Matching
Y. Jiang, K. C. K. Chan, X. Wang, C. C. Loy, Z. Liu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Understanding Deformable Alignment in Video Super-Resolution
K. C. K. Chan, X. Wang, K. Yu, C. Dong, C. C. Loy
in Proceedings of AAAI Conference on Artificial Intelligence, 2021 (AAAI)
[arXiv] [Project Page] -
Cross-Scale Internal Graph Neural Network for Image Super-Resolution
S. Zhou, J. Zhang, W. Zuo, C. C. Loy
in Proceedings of Neural Information Processing Systems, 2020 (NeurIPS)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Non-Local Recurrent Network for Image Restoration
D. Liu, B. Wen, Y. Fan, C. C. Loy, T. S. Huang
in Proceedings of Neural Information Processing Systems, 2018 (NeurIPS)
[PDF] [arXiv] [Project Page] -
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
X. Wang, K. Yu, S. Wu, J. Gu, Y. Liu, C. Dong, C. C. Loy, Y. Qiao, X. Tang
in Workshop Proceedings of European Conference on Computer Vision, 2018 (ECCVW)
[PDF] [arXiv] [Project Page]
Restoration | Enhancement
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Low-Light Image and Video Enhancement Using Deep Learning: A Survey
C. Li, C. Guo, L. Han, J. Jiang, M. Cheng, J. Gu, C. C. Loy
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 (TPAMI)
[DOI] [arXiv] [Project Page] -
Temporally Consistent Video Colorization with Deep Feature Propagation and Self-regularization Learning
Y. Liu, H. Zhao, K. C. K. Chan, X. Wang, C. C. Loy, Y. Qiao, C. Dong
Technical report, arXiv:2110.04562, 2021
[arXiv] -
Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation
X. Pan, X. Zhan, B. Dai, D. Lin, C. C. Loy, P. Luo
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 (TPAMI)
[DOI] [Project Page] -
ReconfigISP: Reconfigurable Camera Image Processing Pipeline
K. Yu, Z. Li, Y. Peng, C. C. Loy, J. Gu
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Path-Restore: Learning Network Path Selection for Image Restoration
K. Yu, X. Wang, C. Dong, X. Tang, C. C. Loy
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 (TPAMI)
[DOI] [arXiv] [Project Page] -
Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
C. Li, C. Guo, C. C. Loy
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 (TPAMI)
[DOI] [arXiv] [Project Page] -
Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Network
R. Feng, C. Li, H. Chen, S. Li, C. C. Loy, J. Gu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Deep Animation Video Interpolation in the Wild
S-Y. Li, S. Zhao, W. Yu, W. Sun, D. Metaxas, C. C. Loy, Z. Liu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation
X. Pan, X. Zhan, B. Dai, D. Lin, C. C. Loy, P. Luo
European Conference on Computer Vision, 2020 (ECCV, Oral)
[PDF] [arXiv] [Project Page] -
Flexible Piecewise Curves Estimation for Photo Enhancement
C. Li, C. Guo, Q. Ai, S. Zhou, C. C. Loy
Technical report, arXiv:2010.13412, 2020
[arXiv] -
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
C. Guo, C. Li, J. Guo, C. C. Loy, J. Hou, S. Kwong, R. Cong
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
X. Wang, C. K. Chan, K. Yu, C. Dong, X. Tang, C. C. Loy
in Workshop Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, NTIRE, 2019 (CVPRW)
[PDF] [arXiv] [Project Page] -
Deep Network Interpolation for Continuous Imagery Effect Transition
X. Wang, K. Yu, C. Dong, X. Tang, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2019 (CVPR)
[PDF] [arXiv] [Project Page]
Optical Flow Estimation
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LiteFlowNet3: Resolving Correspondence Ambiguity for More Accurate Optical Flow Estimation
T.-W. Hui, C. C. Loy
European Conference on Computer Vision, 2020 (ECCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization
T.-W. Hui, X. Tang, C. C. Loy
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 (TPAMI)
[DOI] [arXiv] [Project Page]
Editing and Generation
We like algorithms that could generate new visual contents, e.g., face generation, face reenactment, image inpainting, scene de-occlusion, etc.
Face Manipulation and Editing
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Talk-to-Edit: Fine-Grained Facial Editing via Dialog
Y. Jiang, Z. Huang, X. Pan, C. C. Loy, Z. Liu
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation
H. Zhou, Y. Sun, W. Wu, C. C. Loy, X. Wang, Z. Liu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Pareidolia Face Reenactment
L. Song, W. Wu, C. Fu, C. Qian, C. C. Loy, R. He
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] [YouTube] -
Audio-Driven Emotional Video Portraits
X. Ji, H. Zhou, K. Wang, W. Wu, X. Cao, C. C. Loy, F. Xu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
MEAD: A Large-scale Audio-visual Dataset for Emotional Talking Face Generation
K. Wang, Q. Wu, L. Song, Z. Yang, W. Wu, C. Qian, R. He, Y. Qiao, C. C. Loy
European Conference on Computer Vision, 2020 (ECCV)
[PDF] [Supplementary Material] [Project Page] -
One-shot Face Reenactment
Y. Zhang, S. Zhang, Y. He, C. Li, C. C. Loy, Z. Liu
in Proceedings of British Machine Vision Conference, 2019 (BMVC, Spotlight)
[PDF] [arXiv] [Project Page] -
Instance-level Facial Attributes Transfer with Geometry-aware Flow
W. Yin, Z. Liu, C. C. Loy
in Proceedings of AAAI Conference on Artificial Intelligence, 2019 (AAAI, Spotlight)
[PDF] [arXiv] [Project Page] -
ReenactGAN: Learning to Reenact Faces via Boundary Transfer
W. Wu, Y. Zhang, C. Li, C. Qian, C. C. Loy
in Proceedings of European Conference on Computer Vision, 2018 (ECCV)
[PDF] [arXiv] [Project Page] [YouTube]
Image and Video Generation
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STransGAN: An Empirical Study on Transformer in GANs
R. Xu and X. Xu and K. Chen and B. Zhou and C. C. Loy
Technical report, arXiv:2110.13107, 2021
[arXiv] [Project Page] -
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
L. Jiang, B. Dai, W. Wu, C. C. Loy
in Proceedings of Neural Information Processing Systems, 2021 (NeurIPS)
[PDF] [arXiv] [Project Page] [YouTube] -
Focal Frequency Loss for Image Reconstruction and Synthesis
L. Jiang, B. Dai, W. Wu, C. C. Loy
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
BlockPlanner: City Block Generation with Vectorized Graph Representation
L. Xu, Y. Xiangli, A. Rao, N. Zhao, B. Dai, Z. Liu, D. Lin
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [Supplementary Material] -
Positional Encoding as Spatial Inductive Bias in GANs
R. Xu, X. Wang, K. Chen, B. Zhou, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] [YouTube] -
Scene-aware Generative Network for Human Motion Synthesis
J. Wang, S. Yan, B. Dai, D. Lin
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [Supplementary Material] [Project Page] -
Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs
X. Pan, B. Dai, Z. Liu, C. C. Loy, P. Luo
International Conference on Learning Representations, 2021 (ICLR, Oral)
[PDF] [arXiv] [Project Page] -
Texture Memory-Augmented Deep Patch-Based Image Inpainting
R. Xu, M. Guo, J. Wang, X. Li, B. Zhou, C. C. Loy
IEEE Transactions on Image Processing, 2021 (TIP)
[DOI] [arXiv] -
Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation
X. Pan, X. Zhan, B. Dai, D. Lin, C. C. Loy, P. Luo
European Conference on Computer Vision, 2020 (ECCV, Oral)
[PDF] [arXiv] [Project Page] -
TSIT: A Simple and Versatile Framework for Image-to-Image Translation
L. Jiang, C. Zhang, M. Huang, C. Liu, J. Shi, C. C. Loy
European Conference on Computer Vision, 2020 (ECCV, Spotlight)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Everybody’s Talkin’: Let Me Talk as You Want
L. Song, W. Wu, C. Qian, R. He, C. C. Loy
Technical report, arXiv:2001.05201, 2020
[arXiv] [Project Page] -
Self-Supervised Scene De-occlusion
X. Zhan, X. Pan, B. Dai, Z. Liu, D. Lin, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR, Oral)
[PDF] [arXiv] [Supplementary Material] [Project Page] [YouTube] -
TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting
Z. Yang, W. Zhu, W. Wu, C. Qian, Q. Zhou, B. Zhou, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Real or Not Real, That is the Question
Y. Xiangli, Y. Deng, B. Dai, C. C. Loy, D. Lin
International Conference on Learning Representations, 2020 (ICLR, Spotlight)
[PDF] [Project Page] -
High-Quality Video Generation from Static Structural Annotations
L. Sheng, J. Pan, J. Guo, J. Shao, C. C. Loy
International Journal of Computer Vision, 2020 (IJCV)
[DOI] -
TransGaGa: Geometry-Aware Unsupervised Image-to-Image Translation
W. Wu, K. Cao, C. Li, C. Qian, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2019 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Deep Flow-Guided Video Inpainting
R. Xu, X. Li, B. Zhou, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2019 (CVPR)
[PDF] [arXiv] [Project Page] -
Dense Intrinsic Appearance Flow for Human Pose Transfer
Y. Li, C. Huang, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2019 (CVPR)
[PDF] [Supplementary Material] [Project Page] -
Disentangling Content and Style via Unsupervised Geometry Distillation
W. Wu, K. Cao, C. Li, C. Qian, C. C. Loy
International Conference on Learning Representations Workshop, 2019 (ICLRW)
[PDF]
Audio Generation
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Visually Informed Binaural Audio Generation without Binaural Audios
X. Xu, H. Zhou, Z. Liu, B. Dai, X. Wang, D. Lin
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page]
Image and Video Understanding
We explore effective and efficient methods to detect, segment and recognize objects in complex scenes.
Image Recognition
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Incorporating Convolution Designs into Visual Transformers
K. Yuan, S. Guo, Z. Liu, A. Zhou, F. Yu, W. Wu
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] -
Differentiable Dynamic Wirings for Neural Networks
K. Yuan, Q. Li, S. Guo, D. Chen, A. Zhou, F. Yu, Z. Liu
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF]
Object Detection
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Few-Shot Object Detection via Association and Discrimination
Y. Cao, J. Wang, Y. Jin, T. Wu, K. Chen, Z. Liu, D. Lin
in Proceedings of Neural Information Processing Systems, 2021 (NeurIPS)
[PDF] [arXiv] [Project Page] -
CARAFE++: Unified Content-Aware ReAssembly of FEatures
J. Wang, K. Chen, R. Xu, Z. Liu, C. C. Loy, D. Lin
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 (TPAMI)
[DOI] [arXiv] -
Side-Aware Boundary Localization for More Precise Object Detection
J. Wang, W. Zhang, Y. Cao, K. Chen, J. Pang, T. Gong, J. Shi, C. C. Loy, D. Lin
European Conference on Computer Vision, 2020 (ECCV)
[PDF] [arXiv] [Supplementary Material] -
RGB-D Salient Object Detection with Cross-Modality Modulation and Selection
C. Li, R. Cong, Y. Piao, Q. Xu, C. C. Loy
European Conference on Computer Vision, 2020 (ECCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Feature Pyramid Grids
K. Chen, Y. Cao, C. C. Loy, D. Lin, C. Feichtenhofer
Technical report, arXiv:2004.03580, 2020
[arXiv] -
Prime Sample Attention in Object Detection
Y. Cao, K. Chen, C. C. Loy, D. Lin
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
CARAFE: Content-Aware ReAssembly of FEatures
J. Wang, K. Chen, R. Xu, Z. Liu, C. C. Loy, D. Lin
in Proceedings of International Conference on Computer Vision, 2019 (ICCV, Oral)
[PDF] [arXiv] [Supplementary Material] -
Region Proposal by Guided Anchoring
J. Wang, K. Chen, S. Yang, C. C. Loy, D. Lin
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2019 (CVPR)
[PDF] [arXiv] [Project Page]
Semantic Segmentation
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K-Net: Towards Unified Image Segmentation
W. Zhang, J. Pang, K. Chen, C. C. Loy
in Proceedings of Neural Information Processing Systems, 2021 (NeurIPS)
[PDF] [arXiv] [Project Page] -
FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation
Y. Zang, C. Huang, C. C. Loy
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Seesaw Loss for Long-Tailed Instance Segmentation
J. Wang, W. Zhang, Y. Zang, Y. Cao, J. Pang, T. Gong, K. Chen, Z. Liu, C. C. Loy, D. Lin
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] -
Hybrid Task Cascade for Instance Segmentation
K. Chen, J. Pang, J. Wang, Y. Xiong, X. Li, S. Sun, W. Feng, Z. Liu, J. Shi, W. Ouyang, C. C. Loy, D. Lin
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2019 (CVPR)
[PDF] [arXiv] [Project Page] -
Video Object Segmentation with Joint Re-identification and Attention-Aware Mask Propagation
X. Li, C. C. Loy
in Proceedings of European Conference on Computer Vision, 2018 (ECCV)
[PDF] [arXiv] -
PSANet: Point-wise Spatial Attention Network for Scene Parsing
H. Zhao, Y. Zhang, S. Liu, J. Shi, C. C. Loy, D. Lin, J. Jia
in Proceedings of European Conference on Computer Vision, 2018 (ECCV)
[PDF] [Project Page]
Tracking and Association
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MessyTable: Instance Association in Multiple Camera Views
Z. Cai, J. Zhang, D. Ren, C. Yu, H. Zhao, S. Yi, C. K. Yeo, C. C. Loy
European Conference on Computer Vision, 2020 (ECCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Robust Multi-Modality Multi-Object Tracking
W. Zhang, H. Zhou, S. Sun, Z. Wang, J. Shi, C. C. Loy
in Proceedings of International Conference on Computer Vision, 2019 (ICCV)
[PDF] [arXiv] [Project Page]
Action Recognition
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TAda! Temporally-Adaptive Convolutions for Video Understanding
Z. Huang, S. Zhang, L. Pan, Z. Qing, M. Tang, Z. Liu, M. H. Ang Jr
Technical report, arXiv:2110.06178, 2021
[arXiv] -
Revisiting Skeleton-based Action Recognition
H. Duan, Y. Zhao, K. Chen, D. Shao, D. Lin, B. Dai
Technical report, arXiv:2104.13586, 2021
[arXiv]
3D Scene Understanding and Reconstruction
Our team has been working on various tasks related to 3D reconstruction and perception, e.g, 3D shape generation and 3D human recovery
3D Reconstruction | Completion
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Playing for 3D Human Recovery
Z. Cai, M. Zhang, J. Ren, C. Wei, D. Ren, J. Li, Z. Lin, H. Zhao, S. Yi, L. Yang, C. C. Loy, Z. Liu
Technical report, arXiv:2110.07588, 2021
[arXiv] [Project Page] -
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis
X. Pan, X. Xu, C. C. Loy, C. Theobalt, B. Dai
in Proceedings of Neural Information Processing Systems, 2021 (NeurIPS)
[PDF] [arXiv] [Project Page] -
Garment4D: Garment Reconstruction from Point Cloud Sequences
F. Hong, L. Pan, Z. Cai, Z. Liu
in Proceedings of Neural Information Processing Systems, 2021 (NeurIPS)
[PDF] [Project Page] -
Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion
T. Wu, L. Pan, J. Zhang, T. Wang, Z. Liu, D. Lin
in Proceedings of Neural Information Processing Systems, 2021 (NeurIPS)
[PDF] [arXiv] [Project Page] -
Generative Occupancy Fields for 3D Surface-Aware Image Synthesis
X. Xu, X. Pan, D. Lin, B. Dai
in Proceedings of Neural Information Processing Systems, 2021 (NeurIPS)
[PDF] [arXiv] [Project Page] -
Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements
Y. Rong, J. Wang, Z. Liu, C. C. Loy
in Proceedings of International Conference on 3D Vision, 2021 (3DV)
[arXiv] [Project Page] -
3D Human Texture Estimation from a Single Image with Transformers
X. Xu, C. C. Loy
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV, Oral)
[PDF] [arXiv] [Project Page] -
Variational Relational Point Completion Network
L. Pan, X. Chen, Z. Cai, J. Zhang, H. Zhao, S. Yi, Z. Liu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR, Oral)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Unsupervised 3D Shape Completion through GAN Inversion
J. Zhang, X. Chen, Z. Cai, L. Pan, H. Zhao, S. Yi, C. K. Yeo, B. Dai, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs
X. Pan, B. Dai, Z. Liu, C. C. Loy, P. Luo
International Conference on Learning Representations, 2021 (ICLR, Oral)
[PDF] [arXiv] [Project Page] -
Chasing the Tail in Monocular 3D Human Reconstruction with Prototype Memory
Y. Rong, Z. Liu, C. C. Loy
Technical report, arXiv:2012.14739, 2020
[arXiv] -
Delving Deep into Hybrid Annotations for 3D Human Recovery in the Wild
Y. Rong, Z. Liu, C. Li, K. Cao, C. C. Loy
in Proceedings of International Conference on Computer Vision, 2019 (ICCV)
[PDF] [arXiv] [Project Page] [Supplementary Material]
3D Perception
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Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency
Z. Luo, Z. Cai, C. Zhou, G. Zhang, H. Zhao, S. Yi, S. Lu, H. Li, S. Zhang, Z. Liu
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] [Supplementary Material] -
LiDAR-based Panoptic Segmentation via Dynamic Shifting Network
F. Hong, H. Zhou, X. Zhu, H. Li, Z. Liu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Exploring Data Augmentation for Multi-Modality 3D Object Detection
W. Zhang, Z. Wang, C. C. Loy
Technical report, arXiv:2012.12741, 2020
[arXiv] [Project Page]
Deep Learning
We investigate new deep learning methods that are more efficient, robust, accurate, scalable, transferable, and explainable.
Unsupervised | Self-Supervised Learning
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Self-Supervised Representation Learning: Introduction, Advances and Challenges
L. Ericsson, H. Gouk, C. C. Loy, T. M. Hospedales
Technical report, arXiv:2110.09327, 2021
[arXiv] -
Unsupervised Object-Level Representation Learning from Scene Images
J. Xie, X. Zhan, Z. Liu, Y. S. Ong, C. C. Loy
in Proceedings of Neural Information Processing Systems, 2021 (NeurIPS)
[PDF] [arXiv] [Project Page] -
Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination
X. Wang, Z. Liu, S. X. Yu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Delving into Inter-Image Invariance for Unsupervised Visual Representations
J. Xie, X. Zhan, Z. Liu, Y. S. Ong, C. C. Loy
Technical report, arXiv:2008.11702, 2020
[arXiv] [Project Page] -
Online Deep Clustering for Unsupervised Representation Learning
X. Zhan, J. Xie, Z. Liu, Y. S. Ong, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR)
[PDF] [arXiv] [Project Page] -
Self-Supervised Learning via Conditional Motion Propagation
X. Zhan, X. Pan, Z. Liu, D. Lin, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2019 (CVPR)
[PDF] [arXiv] [Project Page]
Knowledge Distillation
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Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup
G. Xu, Z. Liu, C. C. Loy
Technical report, arXiv:2012.05217, 2020
[arXiv] [Project Page] -
Knowledge Distillation Meets Self-Supervision
G. Xu, Z. Liu, X. Li, C. C. Loy
European Conference on Computer Vision, 2020 (ECCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Residual Knowledge Distillation
M. Gao, Y. Shen, Q. Li, C. C. Loy
Technical report, arXiv:2002.09168, 2020
[arXiv] -
Inter-Region Affinity Distillation for Road Marking Segmentation
Y. Hou, Z. Ma, C. Liu, T.-W. Hui, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Learning Lightweight Lane Detection CNNs by Self Attention Distillation
Y. Hou, Z. Ma, C, Liu, C. C. Loy
in Proceedings of International Conference on Computer Vision, 2019 (ICCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks
Y. Hou, Z. Ma, C. Liu, C. C. Loy
in Proceedings of AAAI Conference on Artificial Intelligence, 2019 (AAAI, Oral)
[PDF] [arXiv] [Project Page] -
An Embarrassingly Simple Approach for Knowledge Distillation
M. Gao, Y. Shen, Q. Li, C. C. Loy, X. Tang
Technical report, arXiv:1812.01819, 2018
[arXiv]
Continual Learning
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Retrospective Class Incremental Learning
Q. Tao, C. C. Loy, J. Cai, Z. Ge, S. See
in Proceedings of IEEE International Conference on Multimedia and Expo, 2021 (ICME)
[PDF] -
Learning a Unified Classifier Incrementally via Rebalancing
S. Hou, X. Pan, C. C. Loy, Z. Wang, D. Lin
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2019 (CVPR)
[PDF] [Project Page] -
Lifelong Learning via Progressive Distillation and Retrospection
S. Hou, X. Pan, C. C. Loy, Z. Wang, D. Lin
in Proceedings of European Conference on Computer Vision, 2018 (ECCV)
[PDF] [Project Page]
Long-Tailed Recognition
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Iterative Human and Automated Identification of Wildlife Images
Z. Miao, Z. Liu, K. M. Gaynor, M. S. Palmer, S. X. Yu, W. M. Getz
Nature Machine Intelligence, vol. 3, pp. 885–895, 2021 (Nat Mach Intell)
[DOI] [arXiv] -
FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation
Y. Zang, C. Huang, C. C. Loy
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Adversarial Robustness under Long-Tailed Distribution
T. Wu, Z. Liu, Q. Huang, Y. Wang, D. Lin
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR, Oral)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Long-Tailed Recognition by Routing Diverse Distribution-Aware Experts
X. Wang, L. Lian, Z. Miao, Z. Liu, S. X. Yu
International Conference on Learning Representations, 2021 (ICLR)
[PDF] [arXiv] [Project Page]
Model Uncertainty and Robustness
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Generalized Out-of-Distribution Detection: A Survey
J. Yang, K. Zhou, Y. Li, Z. Liu
Technical report, arXiv:2110.11334, 2021
[arXiv] [Project Page] -
Semantically Coherent Out-of-Distribution Detection
J. Yang, H. Wang, L. Feng, X. Yan, H. Zheng, W. Zhang, Z. Liu
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Y. Wang, B. Li, T. Che, K. Zhou, D. Li, Z. Liu
in Proceedings of IEEE/CVF International Conference on Computer Vision, 2021 (ICCV)
[PDF] [arXiv] -
Delving Deep into the Generalization of Vision Transformers under Distribution Shifts
C. Zhang, M. Zhang, S. Zhang, D. Jin, Q. Zhou, Z. Cai, H. Zhao, S. Yi, X. Liu, Z. Liu
Technical report, arXiv:2106.07617, 2021
[arXiv] [Project Page] -
Optimization Variance: Exploring Generalization Properties of DNNs
X. Zhang, D. Wu, H. Xiong, B. Dai
Technical report, arXiv:2106.01714, 2021
[arXiv] -
Semi-Supervised Domain Generalization with Stochastic StyleMatch
K. Zhou, C. C. Loy, Z. Liu
in Workshop on Distribution Shifts of Neural Information Processing Systems, 2021 (NeurIPS DistShift)
[arXiv] [Project Page] -
Domain Generalization in Vision: A Survey
K. Zhou, Z. Liu, Y. Qiao, T. Xiang, C. C. Loy
Technical report, arXiv:2103.02503, 2021
[arXiv]
Network Compression
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Network Pruning via Resource Reallocation
Y. Hou, Z. Ma, C. Liu, Z. Wang, C. C. Loy
Technical report, arXiv:2103.01847, 2021
[arXiv] -
EcoNAS: Finding Proxies for Economical Neural Architecture Search
D. Zhou, X. Zhou, W. Zhang, C. C. Loy, S. Yi, X. Zhang, W. Ouyang
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR)
[PDF] [arXiv] [Supplementary Material]
Few-shot Learning
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Learning to Prompt for Vision-Language Models
K. Zhou, J. Yang, C. C. Loy, Z. Liu
Technical report, arXiv:2109.01134, 2021
[arXiv]
Reinforcement Learning
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Safe Exploration by Solving Early Terminated MDP
H. Sun, Z. Xu, M. Fang, Z. Peng, J. Guo, B. Dai, B. Zhou
Technical report, arXiv:2107.04200, 2021
[arXiv]
Media Forensics
We collect large-scale datasets and develop new methods for face forgery detection.
Forgery Detection and Anti-Deepfake
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ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis
Y. He, B. Gan, S. Chen, Y. Zhou, G. Yin, L. Song, L. Sheng, J. Shao, Z. Liu
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR, Oral)
[PDF] [arXiv] [Supplementary Material] [Project Page] -
DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection
L. Jiang, R. Li, W. Wu, C. Qian, C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR)
[PDF] [arXiv] [Supplementary Material] [Project Page]