Wanhua Li

I am a fourth year Ph.D student in the Department of Automation at Tsinghua University, advised by Prof. Jiwen Lu and Prof. Jianjiang Feng .

In 2017, I received my B.S. degree in computer science at Sun Yat-sen University, Guangzhou, China.

My research interests lie in computer vision and deep learning, particularly facial attribute analysis, graph neural networks, and meta learning.

Email  /  CV  /  Google Scholar  /  GitHub

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News

  • 2021-04: One paper on kinship verification is accepted by TIP.
  • 2021-03: Three papers on uncertainty learning, kinship verification, and face clustering are accepted to CVPR 2021.
  • 2020-07: One paper on social relation recognition is accepted to ECCV 2020.
  • 2020-03: One paper on kinship verification is accepted as oral presentation at ICME 2020.
  • 2019-02: One paper on age estimation is accepted to CVPR 2019.
  • Selected Publications

    dise Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical
    Wanhua Li, Jiwen Lu, Abudukelimu Wuerkaixi, Jianjiang Feng, and Jie Zhou
    IEEE Transactions on Image Processing, 2021
    [Paper] [PDF] [bibtex]

    We develop a Hierarchical Reasoning Graph Network (H-RGN) to exploit more powerful and flexible capacity for graph-based kinship verification.

    dise Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression
    Wanhua Li, Xiaoke Huang, Jiwen Lu, Jianjiang Feng, and Jie Zhou
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
    [Website] [arxiv] [Video] [Code]

    We propose probabilistic ordinal embeddings to empower the present-day regression methods with the ability of uncertainty estimation.

    dise Meta-Mining Discriminative Samples for Kinship Verification
    Wanhua Li, Shiwei Wang, Jiwen Lu, Jianjiang Feng, and Jie Zhou
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
    [Website] [arxiv] [Video] [bibtex]

    A Discriminative Sample Meta-Mining strategy is proposed to mine discriminative information from limited positive pairs and sufficient negative samples for kinship verification.

    dise Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 Nodes
    Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, and Jie Zhou
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
    [Website] [arxiv] [Code] [Video]

    It is the first face clustering method to train on very large-scale graph with 20M nodes, and achieve superior inference results on 12M testing data.

    dise Graph-Based Social Relation Reasoning
    Wanhua Li, Yueqi Duan, Jiwen Lu, Jianjiang Feng, and Jie Zhou
    European Conference on Computer Vision (ECCV), 2020
    [Website] [arxiv] [Video] [Code]

    A simpler, faster, and more accurate method for social relation recognition.

    dise Graph-based Kinship Reasoning Network
    Wanhua Li, Yingqiang Zhang, Kangchen Lv, Jiwen Lu, Jianjiang Feng, Jie Zhou
    IEEE International Conference on Multimedia and Expo (ICME), 2020
    Oral Presentation
    [arXiv] [Video] [bibtex]

    We considers how to compare and fuse the extracted feature pair to reason about the kin relations with the proposed graph-based kinship reasoning networks.

    dise BridgeNet: A Continuity-Aware Probabilistic Network for Age Estimation
    Wanhua Li, Jiwen Lu, Jianjiang Feng, Chunjing Xu, Jie Zhou, Qi Tian
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
    [arXiv] [PDF] [bibtex]

    We propose BridgeNet for age estimation, which aims to mine the continuous relation between age labels effectively.

    Honors and Awards

  • 2nd Place in ChaLearn LAP Large-scale Isolated Gesture Recognition Challenge @ICCV 2017.
  • Outstanding Graduate of Sun Yat-Sen University, 2017.
  • National Scholarship, Sun Yat-Sen University, 2014-2015.
  • Professional Activities

  • Reviewer, IEEE Transactions on Image Processing, 2019-.
  • Reviewer, IEEE Transactions on Circuits and Systems for Video Technology, 2019-.
  • Reviewer, IEEE Transactions on Biometrics, Behavior, and Identity Science, 2021-.
  • Reviewer, Pattern Recognition, 2019-.
  • Reviewer, Neural Networks, 2021-.
  • Reviewer, Neurocomputing, 2021-.
  • Reviewer, Pattern Recognition Letters, 2019-.
  • Reviewer, Journal of Visual Communication and Image Representation, 2018-.
  • Reviewer, International Conference on Computer Vision (ICCV), 2021.
  • Reviewer, IEEE International Conference on Multimedia and Expo (ICME), 2019-2021.
  • Reviewer, IEEE International Conference on Image Processing (ICIP), 2018-2021.
  • Reviewer, International Conference on Pattern Recognition (ICPR), 2018-2020.

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