Machine learning · Computer vision
Yanwei Fu 付彦伟
Full Professor (tenured)
School of Data Science, Fudan University
Faculty, Shanghai Innovation Institute
I study how machines learn and generalize from limited data. My research connects few-shot learning and statistical methods with generative models, 3D vision, robotics, and brain decoding.
CVPR Tutorial Organizer & Speaker, 2022–2024
Three consecutive years · Topics & talks →
Selected paper honors
Paper awards & recognition
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2026
Best Paper Award Candidate CVPR 2026 · Oral
Official conference program ↗ -
2026
Top Viewed Article Journal of Advances in Modeling Earth Systems (JAMES)
Coauthored with Kerry Emanuel (MIT; Member of the U.S. National Academy of Sciences and the American Academy of Arts and Sciences), Noah S. Diffenbaugh (Stanford), and Eran Bendavid (Stanford).
Published in 2024 · Recognition announced May 2026
Journal article ↗ -
2025
Long Paper Outstanding Paper Award DeLTa Workshop at ICLR 2025
A Unified Diffusion Bridge Framework via Stochastic Optimal Control
Official award announcement ↗ -
2024
Highest Impact Award IEEE Computer Society Biometrics Workshop
When Person Re-Identification Meets Changing Clothes
Published at the CVPR 2020 Biometrics Workshop · Awarded in 2024
Coauthor's award record ↗ -
2023
Youth Outstanding Paper Award World Artificial Intelligence Conference (WAIC)
SETR: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Coauthored work · Award recipient: Sixiao Zheng
Official award list ↗ -
2019
Best Paper Award IEEE ICME 2019
An End-to-End Architecture for Class-Incremental Object Detection with Knowledge Distillation
Official award announcement ↗ -
2019
Best Paper Finalist CVPR 2019 · Oral
Image Deformation Meta-Networks for One-Shot Learning
Official award announcement ↗
Research awards
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2023
State Natural Science Award, Second Class China
多元协同的视觉计算理论与方法
Team award · Fourth contributor · 2023 award year, announced in 2024
Fudan University announcement ↗ -
2023
Shanghai Technological Invention Award, First Class
面向智能制造的跨域融合感知关键技术及应用
Team award · Third contributor
Shanghai government award list ↗ -
2023
Shanghai Natural Science Award, Second Class
面向行人重识别的高效学习理论与方法
Team award · Fourth contributor
Shanghai government award list ↗ -
2022
Ministry of Education Natural Science Award, First Class China
多元协同的视觉计算理论与方法
Team award · 2022 award year, announced in 2023
Fudan University announcement ↗
Industry recognition
- Outstanding Technical Achievement Award, 2021Huawei Shanghai Research Institute华为上海研究所 · 2021 年度优秀技术成果奖
- Tencent Rhino-Bird Visiting Scholar腾讯“犀牛鸟计划”访问学者
Research
How can models acquire new concepts, transfer knowledge, and generalize with only a few observations? This question underpins my work on learning to learn, from statistical foundations to visual and embodied intelligence.
Few-shot learning & statistical foundations
Meta-learning, sparsity, causal learning, and reliable generalization under limited supervision.
Generative models & 3D vision
Diffusion models, controllable video generation, and 3D/4D reconstruction from sparse observations.
Embodied intelligence
Vision-guided manipulation, vision-language-action models, and learning from demonstrations.
Multimodal learning & brain decoding
Learning across visual, language, and neural signals, including fMRI and EEG representations.
Selected publications
Full publication list →-
CVPR 2026Brain decoding
CineBrain: A Large-Scale Multi-Modal Audiovisual Brain Dataset for Brain-Conditioned Video Generation
Jianxiong Gao, Yichang Liu, Baofeng Yang, Jianfeng Feng, Yanwei Fu
Project & datasetBest Paper Award Candidate · Oral -
ICML 2026Reliable generation
Conformal Reliability: A New Evaluation Metric for Conditional Generation
Yachen Gao, Xinwei Sun, Yikai Wang, Ye Shi, Jingya Wang, Jianfeng Feng, Yanwei Fu
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CVPR 2026Video world models
VerseCrafter: Dynamic Realistic Video World Model with 4D Geometric Control
Sixiao Zheng, Minghao Yin, Wenbo Hu, Xiaoyu Li, Ying Shan, Yanwei Fu
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CVPR 2026Robotics
ActiveVLA: Injecting Active Perception into Vision-Language-Action Models for Precise 3D Robotic Manipulation
Zhenyang Liu, Yongchong Gu, Yikai Wang, Xiangyang Xue, Yanwei Fu
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ICML 2025Spotlight
UniDB: A Unified Diffusion Bridge Framework via Stochastic Optimal Control
Kaizhen Zhu, Mokai Pan, Yuexin Ma, Yanwei Fu, Jingyi Yu, Jingya Wang, Ye Shi
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ICLR 20243D reconstruction
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo
Chenjie Cao, Xinlin Ren, Yanwei Fu
Three consecutive years
CVPR tutorials · 2022–2024
Co-organizer and speaker for three consecutive years, giving opening remarks and tutorial talks at CVPR 2022, 2023, and 2024.
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CVPR 2024
Object-centric Representations in Computer Vision
Talk: More Real-world Applications by Object-centric Representations
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CVPR 2023
Few-shot Learning from Meta-Learning, Statistical Understanding to Applications
Talk: Few-shot Learning by Statistical Methods (with Yikai Wang)
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CVPR 2022
Sparse Learning in Neural Networks and Robust Statistical Analysis
Talks: Introduction; Sparse Learning in Noisy Data Detection (with Yikai Wang)
Academic service
- Action EditorTransactions on Machine Learning Research
- Area Chair, ICML 2023
- CVPR Tutorial Organizer & Speaker2022–2024 · Three consecutive years
Fellowships & honors
- Fellow of the British Computer Society2022 · BCS
- Young Thousand Talents Program2018 · 国家青年千人计划
- Shanghai Eastern Scholar2017 · 上海市东方学者
- ARC DECRA Fellow2016 · Australian Research CouncilDiscovery Early Career Researcher Award
- Chinese Government Award for Outstanding Self-financed Students Abroad2014 · 国家优秀自费留学生奖学金
Academic background
Full Professor, Fudan UniversitySchool of Data Science · Full Professor since December 2023
Postdoctoral Researcher, Disney Research PittsburghWith Leonid Sigal
Ph.D. in Computer Vision, Queen Mary University of LondonAdvisors: Tao Xiang and Shaogang Gong
Master’s degree in Computer Science, Nanjing University
Prospective students & visitors
For research inquiries, doctoral applications, or summer visits, please contact yanweifu@fudan.edu.cn. International students interested in summer internships are welcome to get in touch.
2026 年招生说明：本组仅在复旦大学大数据学院和上海创智学院招生。大数据学院科学硕士及直博生由学院统一招生，请先申请并获得学院 offer，再联系我；申请普博或暑期访问可提前联系。有兴趣研究统计稀疏性的本科生，也可联系孙鑫伟老师共同合作。
本组 2026 年入学的硕士名额已满。