I am an Assistant Professor at the
Department of Computer Science at
The University of Hong Kong. My general research interests cover the broad area of computer vision, machine learning and artificial intelligence, with special emphasis on building intelligent visual systems. My research goal is to utilize artificial intelligence techniques to make machines perceive, understand and interact with the surrounding environment, and ultimately make high positive impacts on various fields.
Previously, I have spent wonderful times as a postdoctoral researcher at
Computer Science and Artificial Intelligence Laboratory (CSAIL) at
MIT, working with
Prof. Antonio Torralba, at
Torr Vision Group at the
University of Oxford (beautiful Oxford), working with
Prof. Philip Torr. I obtained my Ph.D. degree at CSE Department at
The Chinese University of Hong Kong, supervised by
Prof. Jiaya Jia. During Ph.D., I have spent wonderful times as an intern with
Dr. Xiaohui Shen,
Dr. Zhe Lin,
Dr. Kalyan Sunkavalli,
Dr. Brian Price at Adobe (San Jose),
Prof. Raquel Urtasun at Uber (Toronto), and
Dr. Vladlen Koltun at Intel (Santa Clara).
Our current research interests and focus: 1. unified fundamental perception systems (raw operator and backbone); 2. visual content creation, generation, and manipulation (image/video/3d); 3. representation learning, open-world learning, multi-model learning; 4. autonomous driving, embodied ai, robot learning, reinforcement learning etc.
I am looking for self-motivated PhD (2024 intake, multiple positions), Postdoc, Intern, and Visiting Scholar (all year around), working together on exciting and cutting-edge computer vision, machine learning and artificial intelligence projects. If you are interested in working with me, please drop me an email with your resume.
Pinned: Highly optimized codebase available for 3D scene understanding Pointcept (PTv1&PTv2&MSC).
Highly optimized codebase available for semantic segmentation semseg (PSPNet&PSANet).
Unified raw operator for 2D image recognition SAN and 3D point cloud recognition PointTransformerV1, V2.
Unified panoptic segmentation UPSNet (logit level), and PanopticFCN (representation level).
Unified modeling for joint 2D-3D scene recognition BPNet.
Unified tracking architecture UniTrack.
Unified multi-task learning framework MTFormer.
Unified open-world perception system for detection UniDetector and segmentation OPSNet.
Students
Zhenhua Xu (Postdoc, 2023-)
Xi Chen (PhD Student, 2022-)
Yixing Lao (PhD Student, HKUPS, 2022-)
Zhangyang Qi (PhD Student, HKPFS, 2022-)
Xiaoyang Wu (PhD Student, 2022-)
Rongkun Zheng (PhD Student, 2022-)
Muchen Li (Visiting PhD Student from UBC, 2022-)
Zhenyu Wang (Visiting PhD Student from THU, 2022-)
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Masked Scene Contrast: A Scalable Framework for Unsupervised 3D Representation Learning
Xiaoyang Wu, Xin Wen, Xihui Liu, Hengshuang Zhao.
Computer Vision and Pattern Recognition (CVPR), 2023.
[Paper]
[Code]
[Bib]
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Detecting Everything in the Open World: Towards Universal Object Detection
Zhenyu Wang, Yali Li, Xi Chen, Ser-Nam Lim, Antonio Torralba, Hengshuang Zhao, Shengjin Wang.
Computer Vision and Pattern Recognition (CVPR), 2023.
[Paper]
[Code]
[Bib]
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Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners
Zitian Chen, Yikang Shen, Mingyu Ding, Zhenfang Chen, Hengshuang Zhao, Erik Learned-Miller, Chuang Gan.
Computer Vision and Pattern Recognition (CVPR), 2023.
[Paper]
[Bib]
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Point Transformer V2: Grouped Vector Attention and Partition-based Pooling
Xiaoyang Wu, Yixing Lao, Li Jiang, Xihui Liu, Hengshuang Zhao.
Neural Information Processing Systems (NeurIPS), 2022.
[Paper]
[Code]
[Bib]
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MTFormer: Multi-Task Learning via Transformer and Cross-Task Reasoning
Xiaogang Xu*, Hengshuang Zhao*, Vibhav Vineet, Ser-Nam Lim, Antonio Torralba. (*: equal contribution)
European Conference on Computer Vision (ECCV), 2022.
[Paper]
[Code]
[Bib]
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SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness
Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip Torr.
European Conference on Computer Vision (ECCV), 2022.
[Paper]
[Bib]
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DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation
Xin Lai, Zhuotao Tian, Xiaogang Xu, Yingcong Chen, Shu Liu, Hengshuang Zhao, Liwei wang, Jiaya Jia.
European Conference on Computer Vision (ECCV), 2022.
[Paper]
[Code]
[Bib]
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Towards Visual Social Navigation in Photo-realistic Indoor Scenes
Feng Gao, Hengshuang Zhao, Yu Wang.
Robotics: Science and Systems (RSS) Workshop on Social Intelligence in Humans and Robots, 2022.
Ranked 1st place in Embodied AI Social Navigation Challenge 2021.
[Paper]
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FocalClick: Towards Practical Interactive Image Segmentation
Xi Chen, Zhiyan Zhao, Yilei Zhang, Manni Duan, Donglian Qi, Hengshuang Zhao.
Computer Vision and Pattern Recognition (CVPR), 2022.
[Paper]
[Code]
[Bib]
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LAVT: Language-Aware Vision Transformer for Referring Image Segmentation
Zhao Yang, Jiaqi Wang, Yansong Tang, Kai Chen, Hengshuang Zhao, Philip Torr.
Computer Vision and Pattern Recognition (CVPR), 2022.
[Paper]
[Code]
[Bib]
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Generalized Few-shot Semantic Segmentation
Zhuotao Tian, Xin Lai, Li Jiang, Michelle Shu, Hengshuang Zhao, Jiaya Jia.
Computer Vision and Pattern Recognition (CVPR), 2022.
[Paper]
[Code]
[Bib]
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PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer
Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip Torr, Guoying Zhao.
Computer Vision and Pattern Recognition (CVPR), 2022.
[Paper]
[Code]
[Bib]
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Stratified Transformer for 3D Point Cloud Segmentation
Xin Lai, Jianhui Liu, Li Jiang, Liwei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, Jiaya Jia.
Computer Vision and Pattern Recognition (CVPR), 2022.
[Paper]
[Code]
[Bib]
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Prototype-Voxel Contrastive Learning for LiDAR Point Cloud Panoptic Segmentation
Minzhe Liu, Zhou Qiang, Hengshuang Zhao, Jianing Li, Yuan Du, Kurt Keutzer, Li Du, Shanghang Zhang.
International Conference on Robotics and Automation (ICRA), 2022.
[Paper]
[Bib]
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Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision
Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, Yukang Chen, Lu Qi, Liwei Wang, Zeming Li, Jian Sun, Jiaya Jia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
[Paper]
[Code]
[Bib]
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Open World Entity Segmentation
Lu Qi, Jason Kuen, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Philip Torr, Zhe Lin, Jiaya Jia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
[Paper]
[Code]
[Bib]
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Adaptive Perspective Distillation for Semantic Segmentation
Zhuotao Tian, Pengguang Chen, Xin Lai, Li Jiang, Shu Liu, Hengshuang Zhao, Bei Yu, Ming-Chang Yang, Jiaya Jia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
[Paper]
[Bib]
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Patch-based Separable Transformer for Visual Recognition
Shuyang Sun, Xiaoyu Yue, Hengshuang Zhao, Philip Torr, Song Bai.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
[Paper]
[Bib]
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Do Different Tracking Tasks Require Different Appearance Models?
Zhongdao Wang, Hengshuang Zhao, Yali Li, Shengjin Wang, Philip Torr, Luca Bertinetto.
Neural Information Processing Systems (NeurIPS), 2021.
[Project]
[Paper]
[Code]
[Bib]
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Hierarchical Interaction Network for Video Object Segmentation from Referring Expressions
Zhao Yang*, Yansong Tang*, Luca Bertinetto, Hengshuang Zhao, Philip Torr. (*: equal contribution)
British Machine Vision Conference (BMVC), 2021.
[Paper]
[Bib]
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Point Transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip Torr, Vladlen Koltun.
International Conference on Computer Vision (ICCV), 2021. [Oral]
[Paper]
[Code]
[Bib]
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Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation
Xiaogang Xu, Hengshuang Zhao, Jiaya Jia.
International Conference on Computer Vision (ICCV), 2021.
[Paper]
[Code]
[Bib]
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Bidirectional Projection Network for Cross Dimension Scene Understanding
Wenbo Hu*, Hengshuang Zhao*, Li Jiang, Jiaya Jia, Tien-Tsin Wong. (*: equal contribution)
Computer Vision and Pattern Recognition (CVPR), 2021. [Oral]
[Project]
[Paper]
[Code]
[Bib]
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Fully Convolutional Networks for Panoptic Segmentation
Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, Liwei Wang, Zeming Li, Jian Sun, Jiaya Jia.
Computer Vision and Pattern Recognition (CVPR), 2021. [Oral]
[Paper]
[Code]
[Bib]
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Distilling Knowledge via Knowledge Review
Pengguang Chen, Shu Liu, Hengshuang Zhao, Jiaya Jia.
Computer Vision and Pattern Recognition (CVPR), 2021.
[Paper]
[Code]
[Bib]
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PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
Mutian Xu*, Runyu Ding*, Hengshuang Zhao, Xiaojuan Qi. (*: equal contribution)
Computer Vision and Pattern Recognition (CVPR), 2021.
[Paper]
[Code]
[Bib]
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Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip Torr, Li Zhang.
Computer Vision and Pattern Recognition (CVPR), 2021.
[Project]
[Paper]
[Code]
[Bib]
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Semi-supervised Semantic Segmentation with Directional Context-aware Consistency
Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Liwei Wang, Jiaya Jia. (*: equal contribution)
Computer Vision and Pattern Recognition (CVPR), 2021.
[Paper]
[Code]
[Bib]
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Dual-Cross Central Difference Network for Face Anti-Spoofing
Zitong Yu, Yunxiao Qin, Hengshuang Zhao, Xiaobai Li, Guoying Zhao.
International Joint Conference on Artificial Intelligence (IJCAI), 2021.
[Paper]
[Bib]
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Exploring Self-attention for Image Recognition
Hengshuang Zhao, Jiaya Jia, Vladlen Koltun.
Computer Vision and Pattern Recognition (CVPR), 2020.
[Paper]
[Code]
[Bib]
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PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
Li Jiang*, Hengshuang Zhao*, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, Jiaya Jia. (*: equal contribution)
Computer Vision and Pattern Recognition (CVPR), 2020. [Oral]
[Paper]
[Code]
[Bib]
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Prior Guided Feature Enrichment Network for Few-Shot Segmentation
Zhuotao Tian, Hengshuang Zhao†, Michelle Shu, Zhicheng Yang, Ruiyu Li, Jiaya Jia. (†: corresponding authorship)
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
[Paper]
[Code]
[Bib]
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GridMask Data Augmentation
Pengguang Chen, Shu Liu, Hengshuang Zhao, Jiaya Jia.
Technical report, arXiv, 2020.
[Paper]
[Code]
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Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation
Li Jiang, Hengshuang Zhao, Shu Liu, Xiaoyong Shen, Chi-Wing Fu, Jiaya Jia.
International Conference on Computer Vision (ICCV), 2019.
[Paper]
[Bib]
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PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing
Hengshuang Zhao*, Li Jiang*, Chi-Wing Fu, and Jiaya Jia. (*: equal contribution)
Computer Vision and Pattern Recognition (CVPR), 2019.
[Paper]
[Code]
[Video]
[Bib]
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UPSNet: A Unified Panoptic Segmentation Network
Yuwen Xiong*, Renjie Liao*, Hengshuang Zhao*, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun. (*: equal contribution)
Computer Vision and Pattern Recognition (CVPR), 2019. [Oral]
[Paper]
[Code]
[Bib]
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PSANet: Point-wise Spatial Attention Network for Scene Parsing
Hengshuang Zhao*, Yi Zhang*, Shu Liu, Jianping Shi, Chen Change Loy, Dahua Lin, Jiaya Jia. (*: equal contribution)
European Conference on Computer Vision (ECCV), 2018.
Ranked 1st place in WAD Drivable Area Segmentation Challenge 2018.
[Project]
[Paper]
[Caffe]
[PyTorch]
[Video]
[Supp]
[Bib]
[Slides in WAD2018@CVPR2018]
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Compositing-aware Image Search
Hengshuang Zhao, Xiaohui Shen, Zhe Lin, Kalyan Sunkavalli, Brian Price, Jiaya Jia.
European Conference on Computer Vision (ECCV), 2018.
[Project]
[Paper]
[Supp]
[Bib]
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SegStereo: Exploiting Semantic Information for Disparity Estimation
Guorun Yang*, Hengshuang Zhao*, Jianping Shi, Zhidong Deng, Jiaya Jia. (*: equal contribution)
European Conference on Computer Vision (ECCV), 2018.
[Project]
[Paper]
[Code]
[Video]
[Supp]
[Bib]
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ICNet for Real-Time Semantic Segmentation on High-Resolution Images
Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia.
European Conference on Computer Vision (ECCV), 2018.
[Project]
[Paper]
[Code]
[Video]
[Supp]
[Bib]
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Pyramid Scene Parsing Network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia.
Computer Vision and Pattern Recognition (CVPR), 2017.
Ranked 1st place in ImageNet Scene Parsing Challenge 2016.
Ranked 1st place in LSUN Semantic Segmentation Challenge 2017.
[Project]
[Paper]
[Caffe]
[PyTorch]
[Video]
[Bib]
[Slides in ILSVRC2016@ECCV2016]
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Augmented Feedback in Semantic Segmentation under Image Level Supervision
Xiaojuan Qi, Zhengzhe Liu, Jianping Shi, Hengshuang Zhao, Jiaya Jia.
European Conference on Computer Vision (ECCV), 2016.
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Rapid and automatic 3D body measurement system based on a GPU-steger line detector
Xingjian Liu, Hengshuang Zhao, Guomin Zhan, Kai Zhong, Zhongwei Li, YuhJin Chao, Yusheng Shi.
Applied Optics, 2016.
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A high-reflective surface measurement method based on conoscopic holography technology
Xu Cheng, ZhongWei Li, YuSheng Shi, HengShuang Zhao, Guomin Zhan.
Optical Metrology and Inspection for Industrial Applications III, 2014.
Experiences
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2021 – 2022
Postdoc Researcher
Advisor: Antonio Torralba
Topic: Computer Vision, Machine Learning, Artificial Intelligence
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2020 – 2021
Postdoc Researcher
Advisor: Philip Torr
Topic: Computer Vision, Machine Learning, Artificial Intelligence
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2019 – 2020
Research Intern & Visiting Researcher
Advisor: Vladlen Koltun
Topic: Self-attention for Image and Point Cloud Recognition
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2018
Research Intern
Advisor: Raquel Urtasun
Topic: Panoptic Segmentation and Autonomous Driving
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2017
Research Intern
Advisor: Xiaohui Shen, Zhe Lin, Kalyan Sunkavalli and Brian Price
Topic: Compositing-aware Image Search
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2014 – 2015
Undergraduate Research Assistant
Advisor: Zhongwei Li
Topic: 3D Dynamic Measurement and Laser Measurement
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2014
Microsoft Young Fellow
TEDx presentation: "Research on precise 3D measurement technology"
Poster presentation: "Real-time 3D shape measurement system with full temporal resolution and spatial resolution"
Professional Activities
- Program Committee:
Area Chair for Neural Information Processing Systems (NeurIPS), 2023.
Area Chair for IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
Area Chair for IEEE Winter Conference on Applications of Computer Vision (WACV), 2023.
Senior Program Committee for AAI Conference on Artificial Intelligence (AAAI), 2023.
- Conference Reviewer:
IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
IEEE International Conference on Computer Vision (ICCV).
European Conference on Computer Vision (ECCV).
Neural Information Processing Systems (NeurIPS).
International Conference on Machine Learning (ICML).
International Conference on Learning Representations (ICLR).
AAAI Conference on Artificial Intelligence (AAAI).
IEEE Winter Conference on Applications of Computer Vision (WACV).
British Machine Vision Conference (BMVC).
IEEE Intelligent Vehicles Symposium (IV).
Asian Conference on Computer Vision (ACCV).
IEEE International Conference on Robotics and Automation (ICRA).
- Journal Reviewer:
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
International Journal of Computer Vision (IJCV).
ACM Transactions on Graphics (SIGGRAPH).
IEEE Transactions on Image Processing (TIP).
IEEE Transactions on Robotics (T-RO).
IEEE Robotics and Automation Letters (RA-L).
IEEE Transactions on Multimedia (TMM).
IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
Transactions on Machine Learning Research (TMLR).
Pattern Recognition Letters (PRLETTERS).
Journal of Visual Communications and Image Representation (JVCI).
Talks & Presentations
- International Digital Economy Academy (IDEA): "Towards Unified Scene Understanding: Representation, Operator and Framework", May. 2022.
- VALSE Webinar: "Scene Understanding in 3D and 2D-3D", Apr. 2022.
- AI Time Young Scientist: "Towards Unified Scene Understanding: Representation, Operator and Framework", Apr. 2022.
- MIT CSAIL: "Towards Unified Scene Understanding: Representation, Operator and Framework", Nov. 2021.
- MIT CSAIL: "Advancing Visual Intelligence via Neural System Design", Oct. 2021.
- ICCV VSP Workshop, "Towards Unified Scene Understanding: Representation, Operator and Framework", Oct. 2021.
- University of Oxford, Apr. 2021.
- Imperial College London, Mar. 2021.
- University College London, Mar. 2021.
- Max Planck Institute for Informatics, Mar. 2021.
- King Abdullah University of Science and Technology, Mar. 2021.
- University of Southern California, Mar. 2021.
- Tsinghua University, Mar. 2021.
- The Hong Kong University of Science and Technology, Guangzhou, Mar. 2021.
- Microsoft Research: "Advancing Visual Intelligence via Neural System Design", Mar. 2021.
- The University of Hong Kong, Feb. 2021.
- The Chinese University of Hong Kong, Shenzhen, Feb. 2021.
- National University of Singapore, Jan. 2021.
- Nanyang Technological University, Jan. 2021.
- Peking University, Dec. 2020.
- Apple Research: "Pixel-Level Scene Understanding with Segmentation", Nov. 2020.
- Intel Intelligent Systems Lab: "Point Transformer", Oct. 2020.
- Huawei Research UK: "Exploring Self-attention for Image Recognition", Oct. 2020.
- University of Oxford: "Pixel-Level Scene Understanding with Segmentation", Sep. 2020.
- JIANGMEN: "Exploring Self-attention for Image Recognition", Jul. 2020.
- Google Research: "Pixel-Level Scene Understanding with Segmentation", Feb. 2020.
- MIT CSAIL: "Pixel-Level Scene Understanding with Segmentation", Jun. 2019.
- UC Berkeley ICSI: "Pixel-Level Scene Understanding with Segmentation", Jun. 2019.
- UC Berkeley BAIR: "Pixel-Level Scene Understanding with Segmentation", Jun. 2019.
- VALSE Webinar: "Pixel-Level Image Understanding with Semantic Segmentation and Panoptic Segmentation", May 2019.
- Intel Intelligent Systems Lab: "Self-attention Networks for Image Recognition", May 2019.
- Intel Intelligent Systems Lab: "Image Segmentation with Application", Jan. 2019.
- Uber ATG: "Unified Panoptic Segmentation Network (UPSNet): A Unified Framework for Image Understanding", Aug. 2018.
- CVPR WAD Workshop: "IBN-PSANet: Winning WAD Drivable Area Challenge", Jun. 2018.
- VALSE Webinar: "PSPNet and ICNet: Semantic Segmentation with High Accuracy and High Efficiency", Jul. 2017.
- Adobe Bay Area Research Showcase: "Compositing-aware Image Search", Jul. 2017.
- ECCV ILSVRC Workshop: "Understanding Scene in the Wild", Oct. 2016.
Honors & Awards
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2022
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2021
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World Artificial Intelligence Conference (WAIC) Rising Star Award
2020
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ICCV Outstanding Reviewer Award
2019
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NeurIPS Top Reviewer Award
2019
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CVPR Doctoral Consortium Travel Award
2019
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2018
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2017
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2016
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Full Postgraduate Studentship, CUHK
2015
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Outstanding Graduate, HUST
2015
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Microsoft Young Fellowship, Microsoft
2014
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National Encouragement Scholarship, Ministry of Education of P.R. China
2014
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Outstanding Student Cadre, HUST
2014
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Model Student of Academic Record, HUST
2014
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National Scholarship, Ministry of Education of P.R. China
2013
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Merit Student, HUST
2013
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'Dexun' Scholarship, HUST
2013
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Excellent Prize, 'Seed Cup' Competition, HUST
2013
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Second Class Prize, 'Challenge Cup' Competition, National
2013
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First Class Prize, 'Challenge Cup' Competition, Provincial
2013
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First Class Prize, 'Seeking Cup' Competition, HUST
2012
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Freshman Scholarship, HUST
2011
Patents
- US16905478 (In process), "Image processing method, apparatus, electronic device, storage medium, program product".
- US16385333 (In process), "Method and system for scene parsing and storage medium".
- US16929429 (In process), "Compositing aware digital image search".
- CN201810893153 (In process), "Image processing method, apparatus, electronic device, storage medium, program product".
- CN201611097543 (In process), "Scene parsing method and system, electronic equipment".
- US15986401 (Issued Aug. 18, 2020), "Compositing aware digital image search".
- CN201611097445 (Issued Aug. 11, 2020), "Deep neural network training method and system, electronic equipment".
- CN201310233990 (Issued Feb. 24, 2016), "GPU-based object 3D shape measurement method".
- CN201220412358 (Issued Feb. 20, 2013), "Automatic fish tank”.
Teaching
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COMP3314A: Machine Learning
Fall, 2022-2023
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ENGG5103: Techniques for Data Mining
Fall, 2018-2019
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ENGG2601A: Technology, Society and Engineering Practice
Spring, 2017-2018
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ENGG5103: Techniques for Data Mining
Fall, 2017-2018
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CSCI2100B: Data Structures
Spring, 2016-2017
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CSCI3160: Design and Analysis of Algorithms
Fall, 2016-2017
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CSCI2520: Data Structures & Applications
Spring, 2015-2016
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CSCI1120: Introduction to Computing Using C++
Fall, 2015-2016
© Hengshuang Zhao | Last updated: 06/01/2023