Han Hu is currently a principal researcher in Visual Computing Group at Microsoft Research Asia (MSRA). He received the Ph.D degree in 2014 under the supervision of Prof. Jie Zhou and B.S. degree in 2008 from Tsinghua University. His Ph.D dissertation was awarded Excellent Doctoral Dissertation Award of CAAI at 2016. He was a visiting student in University of Pennsylvania under supervision of Prof. Jianbo Shi from October, 2012 to April, 2013. Before he joined MSRA in Dec. 2016, he worked at Institute of Deep Learning (IDL), Baidu Research.
Please drop him an email if you are interested in internship, joint ph.D program or full-time research position.
2021.10 Swin Transformer won ICCV2021 Marr Prize (best paper award).
2021.10 A talk at VALSE2021 Hangzhou about Self-Supervised Learning in Computer Vision: Past, Present, Trends
2021.09 Three spotlight papers accepted by NeurIPS2021.
2021.07 Three papers with one oral accepted by ICCV2021.
2021.6.20 Co-organize the 3rd Tutorial on Learning Representations via Graph-structured Networks, in CVPR2021. Talk title: Swin Transformer and Five Reasons to use Transformer/Attention in Computer Vision [recorded video] [longer version in Chinese 中文]
2021.6.2 A talk at 2021 BAAI: Self-Supervised Learning in Computer Vision: Past, Present, Trends.
2021.5 Code available for Self-Supervised Learning with Swin Transformer.
Will serve as an area chair of CVPR2022.
2021.4 Slides used in recent talks: Toward Universal Models with NLP in Computer Vision.
2021.03 Two papers with one oral accepted by CVPR2021. Code available for PixPro.
2020.11 Chaired the session of "self-supervised learning and transfer learning in vision" on China Pre-conference of NeurIPS2020, and made a talk titled Recent Progress on Self-Supervised Visual Representaion Learning.
2020.09 Three papers with one spotlight accepted by NeurIPS2020.
2020.07 Four papers accepted by ECCV2020.
2020.06.14 Co-organize the 2nd Tutorial on Learning Representations via Graph-structured Networks on CVPR2020. Talk title: Self-Attention Modeling for Visual Recognition [Recorded Video]
2020.01 Invited as an area chair of CVPR2021.
2019.07 A talk at a Valse Webinar, named Towards Universal Learning Machine: Self-Attention for Visual Modeling
GCNet received the best paper award at ICCV 2019 Neural Architects Workshop.
Code available for RepPoints.
Three papers accepted by ICCV 2019.
(†Interns *Equal Contribution)
End-to-End Semi-Supervised Object Detection with Soft Teacher
Mengde Xu*†, Zheng Zhang*, Han Hu, Jianfeng Wang, Lijuan Wang, Fangyun Wei, Xiang Bai, Zicheng Liu
ICCV, 2021 [Arxiv] 61.3 box mAP and 53.0 mask mAP on COCO using Swin-L
Group-Free 3D Object Detection via Transformers
Ze Liu†, Zheng Zhang, Yue Cao, Han Hu, Xin Tong
ICCV, 2021 [Arxiv]
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Ze Liu*†, Yutong Lin*†, Yue Cao*, Han Hu*‡, Yixuan Wei†, Zheng Zhang, Stephen Lin, Baining Guo
ICCV, 2021 (‡ Correspondence) [Arxiv] [Code@Github] Marr Prize (Best Paper Award)
Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
Zhenda Xie*†, Yutong Lin*†, Zheng Zhang, Yue Cao, Stephen Lin, Han Hu
CVPR, 2021 [Arxiv] [Code@Github]
Capsule Network is not More Robust than Convolutional Network
Jindong Gu, Volker Tresp, Han Hu
CVPR, 2021 [Arxiv] Oral
Parametric Instance Classification for Unsupervised Visual Feature Learning
Yue Cao*, Zhenda Xie*†, Bin Liu*†, Yutong Lin†, Zheng Zhang, Han Hu
NeurIPS, 2020 [Arxiv]
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
Yue Cao†*, Jiarui Xu†*, Stephen Lin, Fangyun Wei and Han Hu
In ICCV workshop on Neural Architects, 2019 [Arxiv] [Code] [@mmdet] Best Paper Award
Local Relation Networks for Image Recognition
Han Hu, Zheng Zhang, Zhenda Xie and Stephen Lin
In ICCV, 2019 [Arxiv]
Spatial-Temporal Relation Networks for Multi-Object Tracking
Jiarui Xu†, Yue Cao†, Zheng Zhang, Han Hu
In ICCV, 2019 [Arxiv]
Deformable ConvNets v2: More Deformable, Better Results
Xizhou Zhu†, Han Hu, Stephen Lin and Jifeng Dai
In CVPR, 2019 [Arxiv]
Learning Region Features for Object Detection
Jiayuan Gu†, Han Hu, Liwei Wang, Yichen Wei and Jifeng Dai
In ECCV, 2018 [Arxiv]
Deformable Convolutional Networks
Jifeng Dai*, Haozhi Qi†*, Yuwen Xiong†*, Yi Li†*, Guodong Zhang†*, Han Hu and Yichen Wei
In ICCV, 2017 [Arxiv] Oral
WordSup: Exploiting Word Annotations for Character based Text Detection
Han Hu*, Chengquan Zhang*, Yuxuan Luo, Yuzhuo Wang, Junyu Han and Errui Ding
In ICCV, 2017 [Arxiv]
Depth Estimation using a Sliding Camera
Kailin Ge, Han Hu, Jianjiang Feng and Jie Zhou
In TIP, 2016 [url]
Pose from Flow and Flow from Pose
Katerina Fragkiadaki, Han Hu and Jianbo Shi
In CVPR, 2013 [PDF] Oral
Multi-way Constrained Spectral Clustering via Nonnegative Restriction
Han Hu, Jiahuan Zhou, Jianjiang Feng and Jie Zhou
In ICPR, 2012 [PDF] Oral
Video Stabilization and Completion Using Two Cameras
Jie Zhou, Han Hu and Dingrui Wan
In TCSVT, 2011 [PDF]
HTF: A Novel Feature for General Crack Detection
Han Hu, Quanquan Gu and Jie Zhou
In ICIP, 2010 [PDF] Oral
Trajectory Matching from Unsynchronized Videos
Han Hu and Jie Zhou
In CVPR, 2010 [PDF]
Multiframe Motion Segmentation via Penalized MAP Estimation and Linear Programming
Han Hu, Quanquan Gu, Lei Deng and Jie Zhou
In BMVC, 2009 [PDF] Oral