Wei Hu

Wei Hu (胡玮)

Associate Professor, Ph.D. Supervisor

Peking University Boya Young Fellow

Wangxuan Institute of Computer Technology

Peking University, Beijing, China

IEEE Senior Member

Email: forhuwei AT pku DOT edu DOT cn

I am a tenured associate professsor and independent PI leading the GLab at Wangxuan Institute of Computer Technology, Peking University. I obtained the B.S. degree in Electrical Engineering from University of Science and Technology of China in 2010, and the PhD degree in Electronic and Computer Engineering from The Hong Kong University of Science and Technology in 2015. Before joining Peking University, I was a Researcher in the Imaging Science Laboratory of Technicolor, Rennes, France. Besides, I used to be a visiting student at National Institute of Informatics, Japan, supervised by Prof. Gene Cheung. I have collaborations with Prof. Antonio Ortega from the University of Southern California, Prof. Xin Li from West Virginia University, etc.

My research interests include Graph Signal Processing, Graph-based Machine Learning and their applications in the processing, analysis and synthesis of geometric data and beyond (structural data such as images, network data, brain signals, etc.), which lies at the intersection of signal processing and machine learning. You may click the "Research" tab to know more about my research interests.


Graph Signal Processing (image credit: Catherine Amein)	Graph-based Machine Learning	3D Visual Computing

Positions Opening: We are looking for self-motivated postdocs, graduate students and interns. If you are passionate about our research on Graph Signal Processing and Graph-based Machine Learning with applications in 3D visual computing, please send a detailed CV to me.

News

01/16/2023: 1 TMM paper accepted
09/30/2022: congratulate Daizong Liu for the National Scholarship
08/19/2022: invited to give a talk at CCIG 2022 [slides]
07/21/2022: 1 TPAMI paper accepted
07/04/2022: 2 ECCV papers accepted
06/30/2022: 2 ACM MM papers accepted
06/17/2022: congratulate Bi'an Du for "Excellent Undergraduate" both in Peking University & Beijing
06/17/2022: congratulate Bi'an Du for the Top-10 Excellent Undergraduate Thesis Award in EECS, Peking University
04/27/2022: 1 TPAMI paper accepted
01/12/2022: our ICIP Special Sesstion Proposal "Point cloud compression and processing" has been accepted
12/11/2021: our ICME Special Session proposal on "Advances in Point Cloud Acquisition, Processing and Understanding" has been accepted
12/01/2021: 1 TKDE paper accepted
11/23/2021: 1 TIP paper accepted
11/03/2021: Elected as a member of IEEE Multimedia Signal Processing Technical Committee (MMSP-TC)
09/04/2021: 1 TMM overview paper on "Graph Signal Processing for Geometric Data and Beyond: Theory and Applications" accepted
08/31/2021: 1 TIP paper accepted
08/02/2021: invited to serve as tutorial co-chair for VCIP 2022
07/24/2021: attend APSIPA panel discussion on "Future of Graph Signal Processing”as a panelist
07/23/2021: 1 ICCV paper accepted
07/08/2021: Received the 2021 IEEE Multimedia Rising Star Award-Honorable Mention for "outstanding early-stage career achievements in the area of geometric data processing in the graph domain"
07/08/2021: Received ICME 21' Outstanding Service Award
07/04/2021: 1 ACM MM paper accepted
06/21/2021: 1 TIP paper accepted
06/21/2021: 1 TPAMI paper accepted
06/21/2021: congratulate Shitong Luo for the Top-10 Excellent Undergraduate Thesis Award in EECS, Peking University
06/14/2021: our paper "Diffusion Probabilistic Models for 3D Point Cloud Generation" has been selected as CVPR 2021 Best Paper Candidate
06/06/2021: our paper won Best Poster Award in The CAAI International Conference on Artificial Intelligence
05/04/2021: Appointed as Associate Editor for Signal Processing Magazine
04/20/2021: Elevated to the grade of IEEE Senior member
04/15/2021: Appointed as Associate Editor for Transactions on Signal and Information Processing over Networks
04/09/2021: Our ICCV workshop "When Graph Signal Processing meets Computer Vision" is accepted [link] [PDF]
03/24/2021: Appointed as Associate Editor for Frontiers in Signal Processing
03/01/2021: 2 CVPR papers accepted
02/15/2021: congratulate Shitong Luo who receives an offer from CMU

12/29/2020: 1 TMM paper accepted
12/05/2020: 1 INFOCOM paper accepted
11/24/2020: Appointed Associate Member in MMSP-TC in SPS
11/03/2020: selected as Peking University Boya Young Fellow
08/13/2020: elected as MSA-TC Member (September 1, 2020 to August 31, 2024)
08/03/2020: 1 TCSVT paper accepted
07/26/2020: 1 ACM MM paper accepted
07/10/2020: our paper "3D Dynamic Point Cloud Inpainting via Temporal Consistency on Graphs" won Best Student Paper Runner Up Award in ICME 2020
07/03/2020: 1 ECCV paper accepted
06/23/2020: serve as an Open Source Chair for ICME 2021
06/22/2020: Xiang Gao won President Scholarship, Peking University (2020-2021)
05/30/2020: congratulations for students who receive offers from Cornell Tech, USC, JHU, etc.
05/14/2020: give a talk at 2020 CVPR paper sharing workshop held by MSRA [link]
03/06/2020: 3 ICME papers accepted
03/04/2020: 1 INFOCOM demo paper accepted
02/27/2020: Join the Excutive Area Chair Committee for VALSE
02/25/2020: Join the ACM Multimedia 2020 Reproducibility Committee
02/24/2020: 1 CVPR paper accepted
02/18/2020: 1 TSP paper accepted
02/10/2020: 1 ICASSP paper accepted
01/30/2020: invited as an Area Chair for ACM Multimedia 2020
12/09/2019: give a talk at JD on Graph Neural Networks
12/06/2019: invite Prof. Zhu Li for a talk
10/21/2019: special session proposal for ICME 2020 accepted
08/22/2019: Invited to visit Ryerson University, Toronto
08/08/2019-08/23/2019: Invited to visit York University, Toronto, Canada
07/21/2019: give a talk at USTC on "Graph Convolutional Neural Networks: from perspective of graph signal processing" [Slides]
07/02/2019: 2 ACM Multimedia papers accepted
05/01/2019: 1 ICIP paper accepted
03/10/2019: 1 ICME paper accepted
03/08/2019: 1 TIP paper accepted
10/22/2018: attend ACM MM at Seoul, Korea
10/07/2018: attend ICIP at Athens, Greece
09/07/2018: Prof. Chia-Wen Lin visited us and gave a talk
09/06/2018: 1 AAAI paper submitted
09/04/2018: 1 TIP paper submitted
07/02/2018: 1 ACM MM paper accepted
06/29/2018: 1 GlobalSIP paper submitted
06/22/2018: Xiang Gao won Wangxuan Scholarship, Peking University
05/14/2018 - 05/18/2018: Invited to visit National Institute of Informatics, Tokyo
05/04/2018: 2 ICIP'18 papers accepted
04/27/2018: 1 GSP workshop abstract accepted
04/15/2018: 1 BigMM paper submitted
04/08/2018: 1 ACM MM paper submitted
03/31/2018: 1 GSP workshop abstract submitted
03/19/2018: 1 ACM TOMM paper accepted
03/08/2018: 1 NSFC funding proposal submitted
02/07/2018: 2 ICIP'18 papers submitted
01/30/2018: 1 ICASSP'18 paper accepted
12/15/2017: 1 ICME'18 paper submitted
11/25/2017: MSRA collaborative research proposal accepted
11/06/2017 - 11/10/2017: Invited to visit National Institute of Informatics, Tokyo
10/27/2017: 1 ICASSP'18 paper submitted
10/11/2017: 1 Alibaba Innovative Research (AIR) proposal accepted
09/30/2017: 1 MSRA collaborative research proposal submitted
09/01/2017: One Ph.D. student Xiang Gao and one Master student Zeqing Fu joined our group
08/23/2017: 1 ACM TOMM paper submitted
06/21/2017: 1 MMSP'17 paper accepted
06/15/2017: Selected to be Ph.D. supervisor
04/24/2017: Join Peking University as Assistant Professor

My research interests include Graph Signal Processing (GSP), Graph Neural Network (GNN), as well as the intersection between GSP and GNN for interpretable graph-based machine learning, as described below. Please refer to our overview paper on "Graph Signal Processing for Geometric Data and Beyond: Theory and Applications" [arXiv] for more discussions.

We apply the proposed GSP/GNN paradigms to the processing, analysis and synthesis of geometric data, images, brain signals, etc., with the current focus on geometric data such as 3D point clouds. Below are some major problems we address.

1. Point cloud restoration

Point cloud restoration is an inverse problem to reconstruct point clouds from degraded versions, including denoising, inpainting, upsampling, etc.. As graphs provide structure-adaptive, accurate, and compact representations for geometric data, we focus on point cloud restoration via graph signal processing and graph-based machine learning.


Point cloud denoising	Point cloud upsampling

Selected Relevant Papers:

Haolan Chen, Bi'an Du, Shitong Luo, Wei Hu, "Deep Point Set Resampling via Gradient Fields," accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), May 2022.
Wei Hu, Xiang Gao, Gene Cheung, Zongming Guo, "Feature Graph Learning for 3D Point Cloud Denoising," IEEE Transactions on Signal Processing (TSP), vol. 68, pp. 2841-2856, February 2020.
Wei Hu, Qianjiang Hu, Zehua Wang, Xiang Gao, "Dynamic Point Cloud Denoising via Manifold-to-Manifold Distance," IEEE Transactions on Image Processing (TIP), vol. 30, pp. 6168-6183, July, 2021.
Shitong Luo, Wei Hu, "Score-Based Point Cloud Denoising," International Conference on Computer Vision (ICCV), 2021.

2. Point cloud classification / segmentation

We focus on self-supervised/weakly-supervised/robust graph representation learning for point cloud classification and segmentation.


Point cloud classification (ModelNet)	Point cloud segmentation (ShapeNet)

Selected Relevant Papers:

Xiang Gao, Wei Hu, Guo-Jun Qi, "GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington, June 2020.
Xiang Gao, Wei Hu, Guo-Jun Qi, "Self-Supervised Graph Representation Learning via Topology Transformations," accepted to IEEE Transactions on Knowledge and Data Engineering (TKDE), December, 2021.
Daizong Liu, Wei Hu, "Imperceptible Transfer Attack and Defense on 3D Point Cloud Classification," accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), July 2022.
Gusi Te, Wei Hu, Amin Zheng, Zongming Guo, "RGCNN: Regularized Graph CNN for Point Cloud Segmentation," ACM International Conference on Multimedia (ACM MM), Seoul, Republic of Korea, October 2018.

3. Point cloud generation

Learning generative models for point clouds is powerful in unsupervised representation learning to characterize the data distribution, which lays the foundation for various tasks such as shape completion, upsampling, synthesis, etc.

Selected Relevant papers:

Shitong Luo, Wei Hu, "Diffusion Probabilistic Models for 3D Point Cloud Generation," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2021. [Best Paper Candidate, 1 of 32 chosen from 7015 submissions]

4. Point cloud compression

The large amount of data in 3D point clouds significantly increase the burden for transmission and storage, especially with multiple attributes on each point. Hence, it is quite challenging to represent point clouds compactly, and efficient point cloud compression is required.

Selected Relevant papers:

Yiqun Xu, Wei Hu, Shanshe Wang, Xinfeng Zhang, Shiqi Wang, Siwei Ma, Zongming Guo, Wen Gao, "Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Clouds," IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 31, no. 5, pp. 1968-1982, May 2021.

Current Ph.D. / Master Students


Xiang Gao	Daizong Liu	Gusi Te	Zehua Wang

Qianjiang Hu	Haolan Chen	Bi'an Du	Zhimin Zhang

Co-supervised Ph.D. Student


Yang Liu

#: corresponding author, *: co-first author

Book Chapter

Wei Hu, Siheng Chen, Dong Tian [link]
Graph Spectral Point Cloud Processing
Graph Spectral Image Processing, ISTE/Wiley, June 2021.

Submitted Journal Papers

Xiang Gao, Wei Hu^#, Renjie Liao
Learning Latent Part-Whole Hierarchies for Point Clouds [arXiv]
submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), October, 2022.

Daizong Liu, Wei Hu^#, Xin Li
Point Cloud Attacks in Graph Spectral Domain: When 3D Geometry Meets Graph Signal Processing [arXiv]
submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), July, 2022.

Qianjiang Hu, Wei Hu^#
Dynamic Point Cloud Denoising via Gradient Fields [arXiv]
submitted to IEEE Transactions on Image Processing (TIP), April, 2022.

Zhimin Zhang, Zheng Wang^#, Wei Hu^#
Unsupervised Manga Character Re-identification via Face-body and Spatial-temporal Associated Clustering [arXiv]
submitted to IEEE Transactions on Multimedia (TMM), April, 2022.

Paper Publications

2023

Daizong Liu, Wei Hu^#, Xin Li
Robust Geometry-Dependent Attack for 3D Point Clouds
accepted to IEEE Transactions on Multimedia (TMM), August, 2023.

Wencan Huang, Daizong Liu, Wei Hu^#
Dense Object Grounding in 3D Scenes
accepted to ACM International Conference on Multimedia (ACM MM), 2023

Yunbo Tao, Daizong Liu, Pan Zhou, Yulai Xie, Wei Du, Wei Hu^#
3DHacker: Spectrum-based Decision Boundary Generation for Hard-label 3D Point Cloud Attack
accepted to International Conference on Computer Vision (ICCV), 2023.

Pufan Li, Xiang Gao, Qianjiang Hu, Wei Hu^#
Robust Graph-based Segmentation of Noisy Point Clouds
accepted to IEEE International Conference on Image Processing (ICIP), 2023.

Xiang Gao, Wei Hu^#, Guo-Jun Qi
Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations
accepted to ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP), May, 2023.

Qianjiang Hu, Daizong Liu, Wei Hu^#
Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection
accepted to IEEE Conference on Computer Vision and Pattern Recognition (CVPR), March, 2023.

Daizong Liu, Xiang Fang, Wei Hu^#, Pan Zhou^#
Exploring Optical-Flow-Guided Motion and Detection-Based Appearance for Temporal Sentence Grounding [arXiv]
accepted to IEEE Transactions on Multimedia (TMM), January, 2023.

Jin Zeng, Yang Liu, Gene Cheung, Wei Hu^#
Sparse Graph Learning with Spectrum Prior for Deep Graph Convolutional Networks
accepted to International Conference on Acoustics, Speech, and Signal Processing (ICASSP), January, 2023.

2022

Daizong Liu, Wei Hu^#
Rethinking Graph Neural Networks for Unsupervised Video Object Segmentation
accepted to British Machine Vision Conference (BMVC), 2022

Daizong Liu, Wei Hu^#
Learning to Focus on the Foreground for Temporal Sentence Grounding
accepted to International Conference on Computational Linguistics (COLING), 2022

Daizong Liu, Wei Hu^#
Imperceptible Transfer Attack and Defense on 3D Point Cloud Classification [arXiv]
accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), July, 2022.

Qianjiang Hu^*, Daizong Liu^*, Wei Hu^#
Exploring the Devil in Graph Spectral Domain for 3D Point Cloud Attacks [arXiv][Code]
accepted to European Conference on Computer Vision (ECCV), July 2022.

Gusi Te, Xiu Li, Xiao Li, Jinglu Wang, Wei Hu^#, Yan Lu^#
Neural Capture of Animatable 3D Human from Monocular Video [arXiv]
accepted to European Conference on Computer Vision (ECCV), July 2022.

Daizong Liu, Wei Hu^#
Skimming, Locating, then Perusing: A Human-Like Framework for Natural Language Video Localization [arXiv]
accepted to ACM International Conference on Multimedia (ACM MM), June, 2022.

Daizong Liu, Xiaoye Qu, Wei Hu^#
Reducing the Vision and Language Bias for Temporal Sentence Grounding [Oral]
accepted to ACM International Conference on Multimedia (ACM MM), June, 2022.

Haolan Chen*, Bi'an Du*, Shitong Luo, Wei Hu^#
Deep Point Set Resampling via Gradient Fields [arXiv][Code]
accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), April, 2022.

2021

Xiang Gao, Wei Hu^#, Guo-Jun Qi
Self-Supervised Graph Representation Learning via Topology Transformations [arXiv] [Code]
accepted to IEEE Transactions on Knowledge and Data Engineering (TKDE), December, 2021.

Wenfa Qi, Sirui Guo, Wei Hu^#
Generic Reversible Visible Watermarking Via Regularized Graph Fourier Transform Coding [arXiv]
accepted to IEEE Transactions on Image Processing (TIP), November, 2021.

Wei Hu, Jiahao Pang, Xianming Liu, Dong Tian, Chia-Wen Lin^#, Anthony Vetro
Graph Signal Processing for Geometric Data and Beyond: Theory and Applications [arXiv]
accepted to IEEE Transactions on Multimedia (TMM), September, 2021.

Gusi Te, Wei Hu^#, Yinglu Liu, Hailin Shi, Tao Mei
Adaptive Graph Representation Learning and Reasoning for Face Parsing [arXiv]
accepted to IEEE Transactions on Image Processing (TIP), August, 2021.

Haolan Chen, Shitong Luo, Xiang Gao, Wei Hu^#
Unsupervised Learning of Geometric Sampling Invariant Representations for 3D Point Clouds [PDF]
accepted to IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021.

Shitong Luo, Wei Hu^#
Score-Based Point Cloud Denoising [PDF]
International Conference on Computer Vision (ICCV), 2021.

Bi'an Du^*, Xiang Gao^*, Wei Hu^#, Xin Li
Self-Contrastive Learning with Hard Negative Sampling for Self-supervised Point Cloud Learning [PDF]
accepted to ACM International Conference on Multimedia (ACM MM), July, 2021.

Cheng Yang, Gene Cheung^#, Wei Hu^#
Signed Graph Metric Learning via Gershgorin Disc Alignment [arXiv] [Code]
accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), June, 2021.

Wei Hu^#, Qianjiang Hu, Zehua Wang, Xiang Gao
Dynamic Point Cloud Denoising via Manifold-to-Manifold Distance [arXiv]
accepted to IEEE Transactions on Image Processing (TIP), June, 2021.

Yiming He, Wei Hu^#
3D Hand Pose Estimation via Regularized Graph Representation Learning [PDF] [Best Poster Award]
accepted to The CAAI International Conference on Artificial Intelligence (CICAI), May, 2021.

Qianjiang Hu, Xiao Wang, Wei Hu^#, Guo-Jun Qi^#
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries [PDF] [Code]
accepted to IEEE Conference on Computer Vision and Pattern Recognition (CVPR), March, 2021.

Shitong Luo, Wei Hu^#
Diffusion Probabilistic Models for 3D Point Cloud Generation [PDF] [Code] [Best Paper Candidate, 32 out of 7015 submissions]
accepted to IEEE Conference on Computer Vision and Pattern Recognition (CVPR), March, 2021.

Jiaxiang Tang, Xiang Gao, Wei Hu^#
RGLN: Robust Residual Graph Learning Networks via Similarity-Preserving Mapping on Graphs [PDF]
accepted to International Conference on Acoustics, Speech, and Signal Processing (ICASSP), January, 2021.

2020

Zeqing Fu, Wei Hu^#
Dynamic Point Cloud Inpainting via Spatial-Temporal Graph Learning [PDF] [Invited to the Best Paper Track of TMM]
accepted to IEEE Transactions on Multimedia (TMM), 2020.

Wenquan Xu, Haoyu Song, LinYang Hou, Hui Zheng, Xinggong Zhang, Chuwen Zhang, Wei Hu, Yi Wang, Bin Liu^#
SODA: Similar 3D Object Detection Accelerator at Network Edge for Autonomous Driving
accepted to INFOCOM, 2020.

Yiqun Xu, Wei Hu^#, Shanshe Wang, Xinfeng Zhang, Shiqi Wang, Siwei Ma^#, Zongming Guo, Wen Gao
Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Clouds [PDF]
accepted to IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Aug. 2020.

Shitong Luo, Wei Hu^#
Differentiable Manifold Reconstruction for Point Cloud Denoising [PDF] [Code] [Oral, acceptance rate: 8.89%]
ACM International Conference on Multimedia (ACM MM), Seattle, United States, October 2020.

Gusi Te, Yinglu Liu, Wei Hu^#, Hailin Shi, Tao Mei
Edge-aware Graph Representation Learning and Reasoning for Face Parsing [PDF] [Code]
European Conference on Computer Vision (ECCV), August 2020.

Jie Li, Cong Zhang, Zhi Liu, Wei Sun, Wei Hu, Qiyue Li
Narwhal: a DASH-based Point Cloud Video Streaming System over Wireless Networks [PDF]
IEEE INFOCOM demo, July, Toronto, Canada.

Xiang Gao, Wei Hu^#, Zongming Guo
Exploring Structure-Adaptive Graph Learning for Robust Semi-Supervised Classification [PDF] [Oral]
IEEE International Conference on Multimedia and Expo (ICME), London, July 2020.

Zeqing Fu, Wei Hu^#, Zongming Guo
3D Dynamic Point Cloud Inpainting Via Temporal Consistency on Graphs [PDF] [Best Student Paper Runner Up Award, 5/834 submissions]
IEEE International Conference on Multimedia and Expo (ICME), London, July 2020.

Gusi Te, Wei Hu^#, Zongming Guo
Exploring Hypergraph Representation on Face Anti-spoofing Beyond 2D Attacks [PDF]
IEEE International Conference on Multimedia and Expo (ICME), London, July 2020.

Xiang Gao, Wei Hu^#, Guo-Jun Qi
GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations [PDF] [Code]
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington, June 2020.

Wei Hu^*#, Xiang Gao^*, Gene Cheung, Zongming Guo
Feature Graph Learning for 3D Point Cloud Denoising [PDF] [Code]
IEEE Transactions on Signal Processing (TSP), May, 2020.

Cheng Yang, Gene Cheung, Wei Hu
Fast Graph Metric Learning via Gershgorin Disc Alignment [PDF]
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, May 2020.

2019

Xiang Gao, Wei Hu^#, Jiaxiang Tang, Jiaying Liu, Zongming Guo
Optimized Skeleton-based Action Recognition via Sparsified Graph Regression [PDF]
ACM International Conference on Multimedia (ACM MM), Nice, France, Oct. 21-25, 2019.

Ziling Huang, Zheng Wang^#, Wei Hu^#, Chia-Wen Lin, Shin'Ichi Satoh
DoT-GNN: Domain-Transferred Graph Neural Network for Group Re-identification [PDF]
ACM International Conference on Multimedia (ACM MM), Nice, France, Oct. 21-25, 2019.

Ju He, Zeqing Fu, Wei Hu^#, Zongming Guo
Point Cloud Attribute Inpainting in Graph Spectral Domain [PDF] [Oral]
IEEE International Conference on Image Processing (ICIP), Taiwan, Sept. 22-25, 2019.

Wei Hu^*#, Zeqing Fu^*#, Zongming Guo
Local Frequency Interpretation and Non-Local Self-Similarity on Graph for Point Cloud Inpainting [PDF]
IEEE Transactions on Image Processing (TIP), vol. 28, no. 8, pp. 4087-4100, Aug. 2019

Junkun Qi, Wei Hu^#, Zongming Guo
Feature Preserving and Uniformity-Controllable Point Cloud Simplification on Graph [PDF] [Code] [Oral]
IEEE International Conference on Multimedia and Expo (ICME), Shanghai, Jul. 8-12, 2019.

2018

Gusi Te, Wei Hu^#, Amin Zheng, Zongming Guo
RGCNN: Regularized Graph CNN for Point Cloud Segmentation [PDF] [Code]
ACM International Conference on Multimedia (ACM MM), Seoul, Republic of Korea, Oct. 22-26, 2018.

Xiang Gao, Wei Hu^#, Zongming Guo
Graph-based Point Cloud Denoising [PDF]
IEEE International Conference on Multimedia Big Data (BigMM), Xi'an, China, Sept. 13-16, 2018.

Weihang Liao, Gene Cheung, Wei Hu
Path Coding on Geometric Planar Graph for 2D/3D Visual Data Partitioning [PDF]
IEEE International Conference on Image Processing (ICIP), Athens, Greece, Oct. 7-10, 2018.

Zeqing Fu, Wei Hu^#, Zongming Guo
Point Cloud Inpainting on Graphs from Non-local Self-similarity [PDF]
IEEE International Conference on Image Processing (ICIP), Athens, Greece, Oct. 7-10, 2018.

Wei Hu, Mozhdeh Seifi, Erik Reinhard
Over- and Under-Exposure Reconstruction of a Single Plenoptic Capture [PDF]
ACM Transactions on Multimedia Computing, Communications and Applications (TOMM), vol. 14, no. 2, p. 52, May, 2018.

Yiqun Xu, Wei Hu^#, Shanshe Wang^#, Xinfeng Zhang, Shiqi Wang, Siwei Ma^#, Wen Gao^#
Cluster-Based Point Cloud Coding With Normal Weighted Graph Fourier Transform [PDF]
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Alberta, Canada, Apr. 15-20, 2018

Before 2017

Wei Hu, Mozhdeh Seifi, Erik Reinhard
Optical Center Estimation for Lenslet-based Plenoptic Cameras [PDF]
IEEE International Workshop on Multimedia Signal Processing, Luton, Oct. 16-18, 2017.

Wei Hu, Gene Cheung, Masato Kazui
Graph-based Dequantization of Block-Compressed Piecewise Smooth Images [PDF]
IEEE Signal Processing Letters, vol. 23, no. 2, pp. 242-246, February, 2016. (Patent filed with Samsung Japan.)

Wei Hu, Gene Cheung, Antonio Ortega
Intra-Prediction and Generalized Graph Fourier Transform for Image Coding [PDF] [Code]
IEEE Signal Processing Letters, vol. 22, no. 11, pp. 1913-1917, November, 2015.

Yung-Hsuan Chao, Antonio Ortega, Wei Hu, Gene Cheung
Edge-Adaptive Depth Map Coding with Lifting Transform on Graphs [PDF]
31st Picture Coding Symposium, Cairns, Australia, May 31 - Jun. 3, 2015.

Wei Hu, Gene Cheung, Antonio Ortega, Oscar C. Au
Multi-resolution Graph Fourier Transform for Compression of Piecewise Smooth Images [PDF] [Code]
IEEE Transactions on Image Processing (TIP), vol. 24, no. 1, pp. 419-433, January, 2015.

Jiahao Pang, Gene Cheung, Wei Hu, Oscar C. Au
Redefining Self-Similarity in Natural Images for Denoising Using Graph Signal Gradient [PDF]
Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Siem Reap, city of Angkor Wat, Cambodia, Dec. 9-12, 2014.

Rui Ma, Oscar C. Au, Pengfei Wan, Lingfeng Xu, Wenxiu Sun, Wei Hu
Improved Temporal Psychovisual Modulation for Backward-Compatible Stereoscopic Display [PDF]
IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, Georgia, USA, Dec. 3-5, 2014.

Wei Hu, Gene Cheung, Xin Li, Oscar C. Au
Graph-based Joint Denoising and Super-resolution of Generalized Piecewise Smooth Images [PDF] [Top 10% paper award]
International Conference on Image Processing (ICIP), Paris, France, Oct. 27-30, 2014. (Top 10% paper award.)

Wei Dai, Oscar C. Au, Wenjing Zhu, Pengfei Wan, Wei Hu, Jiantao Zhou
SSIM-based rate-distortion optimization in H.264 [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, May 4-9, 2014.

Wenxiu Sun, Oscar C. Au, Lingfeng Xu, Yujun Li, Wei Hu
Seamless View Synthesis through Texture Optimization [PDF]
IEEE Transactions on Image Processing (TIP), vol. 23, no. 1, pp. 342-355, January, 2014.

Wei Hu, Xin Li, Gene Cheung, Oscar C. Au
Depth Map Denoising using Graph-based Transform and Group Sparsity [PDF] [Code] [Top 10% paper award]
IEEE International Workshop on Multimedia Signal Processing, Pula, Italy, Sept. 30 - Oct. 2, 2013. (Top 10% paper award.)

Wei Dai, Oscar C. Au, Wenjing Zhu, Wei Hu, Pengfei Wan, Jiali Li
A robust interpolation-free approach for sub-pixel accuracy motion estimation [PDF]
IEEE International Conference on Image Processing (ICIP), Melbourne, Australia, Sept. 15-18, 2013.

Chao Pang, Oscar C. Au, Feng Zou, Xingyu Zhang, Wei Hu, Pengfei Wan
Optimal dependent bit allocation for AVS intra-frame coding via successive convex approximation [PDF]
IEEE International Conference on Image Processing (ICIP), Melbourne, Australia, Sept. 15-18, 2013.

Ruobing Zou, Oscar C. Au, Guyue Zhou, Wei Dai, Wei Hu, Pengfei Wan
Personal photo album compression and management [PDF]
IEEE International Symposium on Circuits and Systems (ISCAS), Beijing, China, May 19-23, 2013.

Lingfeng Xu, Oscar C. Au, Wenxiu Sun, Jiali Li, Wei Hu, Rui Ma
Ray-Space based Camera Spacing Correction via Convex Optimization [PDF]
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May 26-31, 2013.

Wenxiu Sun, Oscar C. Au, Lingfeng Xu, Yujun Li, Wei Hu, Zhiding Yu
Texture Optimization for Seamless View Synthesis Through Energy Minimization [PDF]
ACM International Conference on Multimedia (ACM MM), Nara, Japan, Oct. 29 - Nov. 2, 2012.

Wei Hu, Gene Cheung, Xin Li, Oscar C. Au
Depth Map Compression using Multi-resolution Graph-based Transform for Depth-image-based Rendering [PDF]
IEEE International Conference on Image Processing (ICIP), Orland, Florida, U.S.A, Sept. 30 - Oct. 3, 2012. (Patent filed.)

Yujun Li, Oscar C. Au, Lingfeng Xu, Wenxiu Sun, Wei Hu
Inferring Depth from a Pair of Images Captured Using Different Aperture Settings [PDF]
International Conference on Multimedia Modeling, China, September, 2012.

Wei Hu, Gene Cheung, Xin Li, Oscar C. Au
Depth Map Super-resolution Using Synthesized View Matching for Depth-image-based Rendering [PDF]
3rd International Workshop on Hot Topics in 3D (in conjunction with ICME 2012), Melbourne, Australia, July, 2012.

Wei Hu, Oscar C. Au, Lin Sun, Wenxiu Sun, Lingfeng Xu, Yujun Li
Adaptive Depth Map Filter for Blocking Artifacts Removal and Edge Preserving [PDF]
IEEE International Symposium on Circuits and Systems (ISCAS), Seoul, Korea, May 20-23, 2012.

Funded Research Projects

国家重点研发计划，2021YFF0901500，全媒体内容智能生产技术与平台，2021/12-2024/11，1432万元/5900万元，在研，课题二负责人

国家自然科学基金面上项目，61972009，基于谱图理论的多分辨率图卷积神经网络研究，2020/01-2023/12，59万元，在研，主持

国家重点研发计划“科技冬奥”重点专项，2019YFF0302900，冰雪项目交互式多维度观赛体验技术与系统-VR 编码与传输平台，2019/10-2022/06，67/546万元，在研，课题骨干（子项目负责人）

国家重点研发计划，2018YFB1003504，基于异构图计算机的数据管理与分析系统，2018/05-2021/04，25/650万元，在研，课题骨干

北京市自然科学基金青年项目，4194080，基于图谱论的三维点云重建研究，2019/01-2020/12，10万元，在研，主持

北京市自然科学基金-海淀原始创新联合基金项目，19L2133，基于三维点云的混合现实个性化骨关节手术模拟重建，2019/12-2022/12，9/28万元，在研，联合主持

北京大学医学交叉研究种子基金，BMU2018MI016，基于影像的个性化虚拟现实模拟临床手术的研究，2019/01-2019/12，10/20万元，已结题，联合主持

Alibaba Innovation Research，No. XTG201800108，基于图的3D点云压缩，2018/01-2018/12，41万元，已结题，主持

MSRA Collaborative Research, FY18-Research-Sponsorship-029，Graph Neural Networks for 3D Face Anti-spoofing, 2018/01-2018/12，20万元，已结题，主持

北京大学中央高校基本科研业务费专项，7100601213，点云的高效编码，2017/07-2020/12，40万元，在研，主持

Patents

Granted Patents

胡玮，傅泽卿，郭宗明
基于局域平滑性和非局域相似性的三维点云修复方法
2020-10-16，中国，201811610195.6

胡玮，特古斯
一种基于边缘信息和注意力机制的人脸信息识别方法
2020-07-21，中国，202010704678.3

Wei Hu, Erik Reinhard, Mozhdeh Seifi
Method and device for obtaining a HDR image by graph signal processing
2019-07-30, U.S., No. 10366478

Wei Hu, Erik Reinhard, Mozhdeh Seifi
Method and an electronic device for calibrating a plenoptic camera
2019-02-19, U.S., No. 10212321

Gene Cheung, Wei Hu
Encoding device and decoding device for contrast image
2012-06-21, Japan, JP6188005B2

Wenxiu, Sun, Oscar. C. Au, Lingfeng Xu, Yujun Li, Wei Hu, Lu Wang
Apparatus, system, and method for temporal domain hole filling based on background modeling for view synthesis
2012-06-29, U.S., 9235879

Pending Patents

胡玮，高翔，郭宗明
一种三维多视图共变表征学习方法及三维物体识别方法
2021-05-10，中国，202110006861.0

胡玮，高翔，郭宗明
一种无监督图拓扑变换共变表征学习的方法和装置
2021-04-15，中国，202110035423.7

胡玮，杜康晖，郭宗明
点云配准方法和装置
2018-12-12，中国，201811508702.5

胡玮，特古斯，郭宗明
点云的分割方法、装置及计算机存储介质
2018-08-16，中国，201810935634.4

胡玮，傅泽卿，郭宗明
基于图信号处理的点云修复方法、装置及终端
2018-04-08，中国，201810306574.X

胡玮，高翔，郭宗明
点云噪声的去除方法、去噪系统、计算机设备及存储介质
2018-02-08，中国，201810128719.1

马思伟，徐轶群，王苫社，李俊儒，胡玮
一种基于傅里叶图变换的点云帧内编码方法及装置
2017-12-21，WIPO, PCT/CN2017/117856

Introduction to Computation (A), Teaching Assistant, Fall Semester 2017
Graph Signal Processing, Graduate Course, Fall Semester 2018
Graph Neural Networks, Graduate Course, Fall Semester 2019
Graph Signal Processing, Graduate Course, Fall Semester 2019
Graph Neural Networks, Graduate Course, Fall Semester 2020
Graph Signal Processing, Graduate Course, Fall Semester 2020
Graph Neural Networks, Graduate Course, Fall Semester 2021
Graph Signal Processing, Graduate Course, Fall Semester 2021
Data Structure and Algorithms, Spring Semester 2022
Graph Neural Networks, Graduate Course, Fall Semester 2022
Graph Signal Processing, Graduate Course, Fall Semester 2022

Associate Editor for the following Journals

IEEE Signal Processing Magazine
IEEE Transactions on Signal and Information Processing over Networks
Frontiers in Signal Processing

Members of the following Technical Committees

IEEE Multimedia Systems & Applications Technical Committee (MSA-TC) Member
IEEE Multimedia Signal Processing Technical Committee (MMSP-TC) Member

Chairs for the following Conferences

Tutorial Co-Chair for International Conference on Visual Communications and Image Processing (VCIP) 2022
Co-organizer of ICCV 2021 Workshop on "When Graph Signal Processing meets Computer Vision" [link] [PDF]
Special Session Co-organizer for International Conference on Image Processing (ICIP) 2021 [link]
Open Source Co-Chair for International Conference on Multimedia and Expo (ICME) 2021
Area Chair for ACM International Conference on Multimedia (ACM MM) 2020
Special Session Co-organizer for International Conference on Multimedia and Expo (ICME) 2020 [link]
Area Chair for International Conference on Multimedia and Expo (ICME) 2020
Excutive Area Chair for VALSE since 2020
Publicity Chair for IEEE International Conference on Multimedia Big Data 2020
Session Chair for International Conference on Multimedia and Expo (ICME) 2019
Session Chair for IEEE International Conference on Image Processing (ICIP) 2019

Reviewer for the following Journals/Conferences

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
IEEE Transactions on Image Processing (TIP)
IEEE Transactions on Signal Processing (TSP)
IEEE Transactions on Multimedia (TMM)
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
IEEE Signal Processing Letters (SPL)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
ACM International Conference on Multimedia (ACM MM)
AAAI Conference on Artificial Intelligence (AAAI), PC member
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
IEEE International Conference on Image Processing (ICIP)
International Conference on Multimedia and Expo (ICME)
International Workshop on Multimedia Signal Processing (MMSP)