Guangyi Chen

I am a fifth year Ph.D student in the Department of Automation at Tsinghua University, advised by Prof. Jie Zhou and Prof. Jiwen Lu . In 2016, I obtained my B.Eng. in the Department of Automation, Tsinghua University.

I am broadly interested in computer vision and deep learning. My current research focuses on attention learning, causal reasoning, video understanding, and person re-identification.

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News

  • 2021-7: 1 paper on person re-identification and attention learning is accepted by TIP'2021.
  • 2021-7: 3 paper on trajectory prediction and attention learning is accepted by ICCV'2021.
  • 2021-3: 1 paper on unintentional action localization is accepted by ICME'2021.
  • 2020-7: 2 papers on person re-identification are accepted by ECCV'2020.
  • 2020-06: Our team pangpang (I and Yongming) won the 2nd place in Semi-Supervised Recognition Challenge at FGVC7 (CVPR 2020).
  • 2020-05: 1 paper is accepted by TIP.
  • 2019-07: 2 papers are accepted by ICCV'2019.
  • 2019-03: 1 paper is accepted by TIP.
  • Publications

    * indicates equal contribution

    dise Person Re-identification via Attention Pyramid
    Guangyi Chen, Tianpei Gu, Jiwen Lu, Jin-An Bao, and Jie Zhou
    IEEE Transactions on Image Processing (TIP), 2021
    [PDF] [Supp] [Code]

    We propose attention pyramid networks by the "split-attend-merge-stack" principle to jointly learn the attentions under different scales and obtain superior performance on many person re-identification datasets.

    dise Temporal Label Aggregation for Unintentional Action Localization
    Nuoxing Zhou, Guangyi Chen, Jinglin Xu, Weishi Zheng, and Jiwen Lu
    2021 IEEE International Conference on Multimedia and Expo (ICME), 2021
    [PDF]

    We formulate the unintentional action localization as a temporal probabilistic regression problem, and propose to online aggregate multiple annotations using an attention model.

    dise Temporal Coherence or Temporal Motion: Which is More Critical for Video-based Person Re-identification?
    Guangyi Chen*, Yongming Rao*, Jiwen Lu and Jie Zhou
    Proceedings of the European Conference on Computer Vision (ECCV), 2020
    [PDF]

    We show temporal coherence plays a more critical role than temporal motion for video-based person ReID and develop an adversarial feature augmentation to highlight temporal coherence.

    dise Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification
    Guangyi Chen, Yuhao Lu, Jiwen Lu and Jie Zhou
    16th European Conference on Computer Vision (ECCV), 2020
    [PDF]

    We propose to adaptively and progressively mine credible training samples to avoid the damage from the noise of predicted pseudo labels for unsupervised domain adaptation person ReID.

    dise Deep Meta Metric Learning
    Guangyi Chen, Tianren Zhang, Jiwen Lu and Jie Zhou
    IEEE International Conference on Computer Vision (ICCV), 2019
    [PDF] [Code]

    We propose to understand the deep metric learning via meta-learning.

    dise Self-Critical Attention Learning for Person Re-Identification
    Guangyi Chen, Chunze Lin, Liangliang Ren, Jiwen Lu and Jie Zhou
    IEEE International Conference on Computer Vision (ICCV), 2019
    [PDF]

    We present a self-critical attention learning method which applies a critic module to examine and surpervise the attention model.

    dise Learning Recurrent 3D Attention for Video-Based Person Re-identification
    Guangyi Chen, Jiwen Lu, Ming Yang, and Jie Zhou
    IEEE Transactions on Image Processing (TIP), 2020
    [PDF]

    We propose to recurrently discover the 3D attention regions and use the reinforcement learning for optimization.

    dise Spatial-Temporal Attention-aware Learning for Video-based Person Re-identification
    Guangyi Chen, Jiwen Lu, Ming Yang, and Jie Zhou
    IEEE Transactions on Image Processing (TIP), 2019
    [PDF]

    We propose a spatial-temporal attention to jointly discover the salient clues in both spatial and temporal domain.

    dise Localized multi-kernel discriminative canonical correlation analysis for video-based person re-identification
    Guangyi Chen, Jiwen Lu, Jianjiang Feng, and Jie Zhou
    IEEE International Conference on Image Processing (ICIP), 2017
    [PDF]

    We model each pedestrian video as a point on the Riemannian manifold and learn similarity over these points under the multiple kernel learning framework.

    Competition Awards

  • 2nd place in Semi-Supervised Recognition Challenge at FGVC7 (CVPR 2020)
  • Academic Services

  • Co-organizer: for the ICME 2019 workshop: The Third Workshop on Human Identification in Multimedia (HIM'19) [website]
  • Conference Reviewer / Program Committee Member: CVPR, ICML, ICCV, NeurIPS and so on.
  • Journal Reviewer: TIP, TMM, TCSVT and so on.

  • Website Template


    © Guangyi Chen | Last updated: Feb 20, 2021