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

  • 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)
    [arXiv] [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)
    [arXiv] [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)
    [arXiv] [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]
  • 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] [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

  • 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
    Technical report, arXiv:2104.10729, 2021
    [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)
    [arXiv] [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)
    [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]
  • Path-Restore: Learning Network Path Selection for Image Restoration
    K. Yu, X. Wang, C. Dong, X. Tang, C. C. Loy
    Technical report, arXiv:1904.10343, 2019
    [arXiv] [Project Page]

Optical Flow Estimation

  • 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

  • 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)
    [arXiv] [Project Page]
  • Everything’s Talkin’: 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] [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)
    [arXiv] [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

  • 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)
    [arXiv] [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] [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]
  • Focal Frequency Loss for Image Reconstruction and Synthesis
    L. Jiang, B. Dai, W. Wu, C. C. Loy
    Technical report, arXiv:2012.12821, 2020
    [arXiv] [Project Page]
  • Texture Memory-Augmented Deep Patch-Based Image Inpainting
    R. Xu, M. Guo, J. Wang, X. Li, B. Zhou, C. C. Loy
    Technical report, arXiv:2009.13240, 2020
    [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] [Supplementary Material] [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

  • 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)
    [arXiv] [Project Page]

Image and Video Understanding

We explore effective and efficient methods to detect, segment and recognize objects in complex scenes.

Image Recognition

  • Incorporating Convolution Designs into Visual Transformers
    K. Yuan, S. Guo, Z. Liu, A. Zhou, F. Yu, W. Wu
    Technical report, arXiv:2103.11816, 2021
    [arXiv]

Object Detection

  • 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

  • FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation
    Y Zang, C. Huang, C. C. Loy
    Technical report, arXiv:2102.12867, 2021
    [arXiv]
  • 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)
    [arXiv]
  • 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

  • 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

  • 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

  • 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)
    [arXiv] [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)
    [arXiv] [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

  • 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)
    [arXiv] [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

  • Unsupervised Feature Learning by Cross-Level Discrimination between Instances and Groups
    X. Wang, Z. Liu, S. X. Yu
    in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2021 (CVPR)
    [arXiv] [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

  • 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

  • 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

  • FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation
    Y Zang, C. Huang, C. C. Loy
    Technical report, arXiv:2102.12867, 2021
    [arXiv]
  • 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)
    [arXiv] [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]

Domain Generalization

  • 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]
  • 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
    Technical report, arXiv:2106.00592, 2021
    [arXiv] [Project Page]
  • Domain Generalization: A Survey
    K. Zhou, Z. Liu, Y. Qiao, T. Xiang, C. C. Loy
    Technical report, arXiv:2103.02503, 2021
    [arXiv]

Network Compression

  • 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]

Media Forensics

We collect large-scale datasets and develop new methods for face forgery detection.

Forgery Detection and Anti-Deepfake

  • 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)
    [arXiv] [Project Page]
  • DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection
    L. Jiang, W. Wu, R. Li, C. Qian, C. C. Loy
    in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2020 (CVPR)
    [PDF] [arXiv] [Supplementary Material] [Project Page]