General

Fang Wan, Assistant Professor & Ph.D. Advisor

Fang Wan is an Assistant Professor and Ph.D. Advisor at the School of Computer Science and Technology, University of Chinese Academy of Sciences (UCAS). He was selected for the China Postdoctoral Innovative Talent Support Program and received the Excellent Doctoral Dissertation Award of the Chinese Academy of Sciences. His research interests include computer vision, multimodal learning and understanding, and learning with limited supervision. He has published more than 40 papers in leading international conferences, including CVPR, ICCV, NeurIPS, AAAI, and ECCV, and in prestigious journals such as IEEE TPAMI, TNNLS, TIP, TCSVT, Pattern Recognition, and IEEE TGRS. He received the Second Prize of the National Technological Invention Award in 2023 (ranked fifth) and the First Prize of the Natural Science Award of the Chinese Institute of Electronics (ranked fourth). He was also named a Xiaomi Young Scholar in 2023 and serves as a Postdoctoral Co-supervisor at Alibaba DAMO Academy. He has served as the principal investigator of a Key Deployment Project of the Chinese Academy of Sciences and three national-level research projects, including grants from the Young Scientists Fund and the General Program of the National Natural Science Foundation of China (NSFC).


Email: wanfang@ucas.ac.cn

Google Scholar: https://scholar.google.com/citations?user=0IKavloAAAAJ

Lab: Machine Learning and Perception Laboratory (LAMP) — http://lamp.ucas.ac.cn/

Research Areas

Computer Vision

Multimodal Learning and Understanding

Learning with Limited Supervision

Education

2016.09–2019.06 Ph.D., University of Chinese Academy of Sciences

2013.09–2016.06 M.S., University of Chinese Academy of Sciences

2009.09–2013.06 B.S., Wuhan University

Experience

Dec. 2021 – Present, Assistant Professor, University of Chinese Academy of Sciences

Jul. 2019 – Dec. 2021, Postdoctoral Researcher, University of Chinese Academy of Sciences

Mar. 2019 – Jun. 2019, Research Intern, Microsoft Research Asia

Publications

Selected Publications

  1. Di Zhu, Ziheng Yan, Fang Wan*. ActionUNet: Improving Robustness of VLA Models with Efficient Multi-scale Fine-tuning. Advances in Neural Information Processing Systems (NeurIPS), 2026. To appear.
  2. Yuzhong Zhao, Yue Liu, Junpeng Liu, Jingye Chen, Xun Wu, Yaru Hao, Tengchao Lv, Shaohan Huang, Lei Cui, Qixiang Ye, Fang Wan*, Furu Wei*. Geometric-Mean Policy Optimization. International Conference on Learning Representations (ICLR), 2026.
  3. Da Peng, Xuesong Yang, Zonghao Guo, Yichen Zhang, Chi Chen, Yidan Zhang, Yuan Yao, Fang Wan*, Wei Ke*, Maosong Sun. FlexiVideo: Variation-Aware Temporal Dynamics Modeling for Efficient Video Understanding. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  4. Ziheng Yan, Xinyan Liu, Guorong Li, Weigang Zhang, Fang Wan, Qingming Huang. Compactness Driven Co-learning for Crowd Counting and Localization. Pattern Recognition, 179: 113638, 2026.
  5. Feng Liu, Shiwei Zhang, Xiaofeng Wang, Yujie Wei, Haonan Qiu, Yuzhong Zhao, Yingya Zhang, Qixiang Ye, Fang Wan*. Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025. Highlight.
  6. Yuzhong Zhao, Feng Liu, Yue Liu, Mingxiang Liao, Chen Gong, Qixiang Ye, Fang Wan. DynRefer: Delving into Region-level Multimodal Tasks via Dynamic Resolution. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
  7. Mingxiang Liao, Fang Wan, Zonghao Guo, Qixiang Ye. Hierarchical AttentionShift for Pointly Supervised Instance Segmentation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 36(8): 15528–15541, 2025.
  8. Zonghao Guo, Fang Wan, Mingxiang Liao, Yidan Zhang, Qixiang Ye. Discriminatively Matched Part Tokens for Pointly Supervised Instance Segmentation. International Journal of Computer Vision (IJCV), 133(11): 7855–7872, 2025.
  9. Mingxiang Liao, Hannan Lu, Xinyu Zhang, Fang Wan, Tianyu Wang, Yuzhong Zhao, Wangmeng Zuo, Qixiang Ye, Jingdong Wang. Evaluation of Text-to-Video Generation Models: A Dynamics Perspective. Advances in Neural Information Processing Systems (NeurIPS), 2024.
  10. Yuzhong Zhao, Yue Liu, Zonghao Guo, Weijia Wu, Chen Gong, Qixiang Ye, Fang Wan*. ControlCap: Controllable Region-level Captioning. European Conference on Computer Vision (ECCV), 2024.
  11. Feng Liu, Tengteng Huang, Qianjing Zhang, Haotian Yao, Chi Zhang, Fang Wan, Qixiang Ye, Yanzhao Zhou. Ray Denoising: Depth-Aware Hard Negative Sampling for Multi-view 3D Object Detection. European Conference on Computer Vision (ECCV), 2024.
  12. Fang Wan, Qixiang Ye, Tianning Yuan, Songcen Xu, Jianzhuang Liu, Xiangyang Ji, Qingming Huang. Multiple Instance Differentiation Learning for Active Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(10): 12133–12147, 2023.
  13. Yuzhong Zhao, Qixiang Ye, Weijia Wu, Chunhua Shen, Fang Wan. Generative Prompt Model for Weakly Supervised Object Localization. IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  14. Feng Liu, Xiaosong Zhang, Zhiliang Peng, Zonghao Guo, Fang Wan, Xiangyang Ji, Qixiang Ye. Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection. IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  15. Mingxiang Liao, Zonghao Guo, Yuze Wang, Peng Yuan, Bailan Feng, Fang Wan. AttentionShift: Iteratively Estimated Part-Based Attention Map for Pointly Supervised Instance Segmentation. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  16. Mingxiang Liao, Fang Wan*, Yuan Yao, Zhenjun Han, Jialing Zou, Yuze Wang, Bailan Feng, Peng Yuan, Qixiang Ye. End-to-End Weakly Supervised Object Detection with Sparse Proposal Evolution. European Conference on Computer Vision (ECCV), 2022.
  17. Xiaosong Zhang, Fang Wan, Chang Liu, Xiangyang Ji, Qixiang Ye. Learning to Match Anchors for Visual Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 44(6): 3096–3109, 2022.
  18. Boyu Yang, Fang Wan*, Chang Liu, Bohao Li, Xiangyang Ji, Qixiang Ye. Part-Based Semantic Transform for Few-Shot Semantic Segmentation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 33(12): 7141–7152, 2022.
  19. Qixiang Ye, Fang Wan*, Chang Liu, Qingming Huang, Xiangyang Ji. Continuation Multiple Instance Learning for Weakly and Fully Supervised Object Detection. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 33(10): 5452–5466, 2022.
  20. Wei Gao, Fang Wan*, Xingjia Pan, Zhiliang Peng, Qi Tian, Zhenjun Han, Bolei Zhou, Qixiang Ye*. TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization. IEEE/CVF International Conference on Computer Vision (ICCV), 2021.
  21. Tianning Yuan, Fang Wan*, Mengying Fu, Jianzhuang Liu, Songcen Xu, Xiangyang Ji, Qixiang Ye*. Multiple Instance Active Learning for Object Detection. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  22. Mengying Fu, Tianning Yuan, Fang Wan*, Songcen Xu, Qixiang Ye*. Agreement-Discrepancy-Selection: Active Learning with Progressive Distribution Alignment. AAAI Conference on Artificial Intelligence (AAAI), 2021.
  23. Xiaosong Zhang, Fang Wan, Chang Liu, Rongrong Ji, Qixiang Ye. FreeAnchor: Learning to Match Anchors for Visual Object Detection. Advances in Neural Information Processing Systems (NeurIPS), 2019.
  24. Fang Wan, Chang Liu, Wei Ke, Xiangyang Ji, Jianbin Jiao, Qixiang Ye. C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019. Oral.
  25. Fang Wan, Pengxu Wei, Jianbin Jiao, Zhenjun Han, Qixiang Ye. Min-Entropy Latent Model for Weakly Supervised Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41(10): 2395–2409, 2019.
  26. Haolan Xue, Chang Liu, Fang Wan*, Jianbin Jiao, Qixiang Ye*. DANet: Divergent Activation for Weakly Supervised Object Localization. IEEE/CVF International Conference on Computer Vision (ICCV), 2019.
  27. Caijing Miao, Lingxi Xie, Fang Wan, Chi Su, Hongye Liu, Jianbin Jiao, Qixiang Ye. SIXray: A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

* Corresponding author.