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Fan Yue

Ph.D. Student
Max Planck Institute for Informatics
yfan (at) mpi-inf.mpg.de


Short Bio

I am currently a Ph.D. student in Computer Vision and Machine Learning group at Max Planck Institute for Informatics, advised by Prof. Bernt Schiele. My research involves close collaborations with Dr. Dengxin Dai. During my PhD, I was a student researcher at Google Zurich, working with Dr. Yongqin Xian, Dr. Xiaohua Zhai (DeepMind), Dr. Alexander A. Kolesnikov (DeepMind), and Prof. Federico Tombari. Prior to this, I obtained my Master’s degree from Saarland University.

My research goal is to build intelligent machines that can perceive and understand the world as humans, with a special focus on learning representations of our visual world. So far, my primary focus has been on tackling it through a data-centric lens. That is, how can we learn good representations from imperfect data? Moving forward, I am excited to explore the following research questions:

I am currently on the job market, looking for postdoctoral and industry positions related to Computer Vision and Machine Learning. Please feel free to contact me if you are interested. I am also happy to give talks on my research in related seminars.

News

Publications

  1. ICCV
    SSB: Simple but Strong Baseline for Boosting Performance of Open-Set Semi-Supervised Learning
    Yue Fan, Anna Kukleva, Dengxin Dai, Bernt Schiele
    IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
    PDF Code

  2. ICLR
    Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning
    Hao Chen, Ran Tao, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Bhiksha Raj, Marios Savvides
    The Eleventh International Conference on Learning Representations (ICLR), 2023.
    PDF Code

  3. ICLR
    FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
    Yidong Wang, Hao Chen, Qiang Heng, Wenxin Hou, Yue Fan, Zhen Wu, Jindong Wang, Marios Savvides, Takahiro Shinozaki, Bhiksha Raj, Bernt Schiele, Xing Xie
    The Eleventh International Conference on Learning Representations (ICLR), 2023.
    PDF Code

  4. NeurIPS
    Usb: A unified semi-supervised learning benchmark for classification
    Yidong Wang*, Hao Chen*, Yue Fan*, SUN Wang, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang
    (* Equal contribution)
    Advances in Neural Information Processing Systems (NeurIPS), 2022.
    PDF Code

  5. CVPR
    CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning
    Yue Fan, Dengxin Dai, Anna Kukleva, Bernt Schiele
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
    PDF Code

  6. IJCV
    Revisiting consistency regularization for semi-supervised learning
    Yue Fan, Anna Kukleva, Dengxin Dai, Bernt Schiele
    International Journal of Computer Vision (IJCV) 2023.
    PDF

  7. GCPR
    Analyzing the dependency of convnets on spatial information
    Yue Fan, Yongqin Xian, Max Maria Losch, Bernt Schiele
    Pattern Recognition, 42nd DAGM German Conference, DAGM GCPR (GCPR) 2020.
    PDF

  8. Parameter-free spatial attention network for person re-identification
    Haoran Wang*, Yue Fan*, Zexin Wang, Licheng Jiao, Bernt Schiele
    (* Equal contribution)
    arXiv 2018.
    PDF

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Contact

Address: Max-Planck-Institut für Informatik, Campus, 66123, Saarbrücken
Office Location: E1 4 - 608
Email: yfan (at) mpi-inf.mpg.de
Phone: +49 681 9325 2138