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Yaoyao Liu

Postdoctoral Fellow
Johns Hopkins University
yliu538 (at) jhu.edu


Short Bio

I am currently a postdoctoral fellow in the Department of Computer Science at Johns Hopkins University. I am fortunate to work with Prof. Alan L. Yuille. I received my Ph.D. in Computer Science at Max Planck Institute for Informatics, where I was fortunate to be advised by Prof. Bernt Schiele and Prof. Qianru Sun. As part of the European Laboratory for Learning and Intelligent Systems (ELLIS) Ph.D. Program, I was also co-supervised by Prof. Christian Rupprecht and Prof. Andrea Vedaldi in the Visual Geometry Group (VGG) at the University of Oxford. From 2018 to 2019, I was a research intern at the National University of Singapore, working with Prof. Tat-Seng Chua and Prof. Qianru Sun. Prior to this, I obtained my bachelor’s degree from Tianjin University.

My research lies at the intersection of computer vision and machine learning – with a special focus on building intelligent visual systems that are continual and data-efficient. My research interests include continual learning, few-shot learning, semi-supervised learning, generative models, 3D geometry models, and medical imaging.

I am currently on the 2023-2024 academic job market, looking for faculty positions in CS, CSE, ECE, IEOR, etc., related to Artificial Intelligence, 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 [Google Scholar][DBLP]

  1. Preprint
    Adding 3D Geometry Control to Diffusion Models
    Wufei Ma*, Qihao Liu*, Jiahao Wang*, Xiaoding Yuan, Angtian Wang, Yi Zhang, Zihao Xiao, Guofeng Zhang, Beijia Lu, Ruxiao Duan, Yongrui Qi, Adam Kortylewski, Yaoyao Liu, Alan Yuille
    ( Corresponding author)
    Under review.
    PDF BibTex

  2. MICCAI
    Continual Learning for Abdominal Multi-Organ and Tumor Segmentation
    Yixiao Zhang, Xinyi Li, Huimiao Chen, Alan Yuille, Yaoyao Liu, Zongwei Zhou
    ( Corresponding authors)
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023.
    PDF Code BibTex Early Accept

  3. CVPR
    Continual Detection Transformer for Incremental Object Detection
    Yaoyao Liu, Bernt Schiele, Andrea Vedaldi, Christian Rupprecht
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
    PDF Code Project Page BibTex

  4. CVPR
    Class-Incremental Exemplar Compression for Class-Incremental Learning
    Zilin Luo, Yaoyao Liu, Bernt Schiele, Qianru Sun
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
    PDF Code Project Page BibTex

  5. AAAI
    Online Hyperparameter Optimization for Class-Incremental Learning
    Yaoyao Liu, Yingying Li, Bernt Schiele, Qianru Sun
    AAAI Conference on Artificial Intelligence (AAAI), 2023.
    PDF Code Project Page BibTex Oral Presentation

  6. TPAMI
    Meta-Transfer Learning through Hard Tasks
    Qianru Sun*, Yaoyao Liu*, Zhaozheng Chen, Tat-Seng Chua, Bernt Schiele
    (* Equal contribution)
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Volume 44, Number 3, 2022.
    PDF Code Project Page BibTex

  7. NeurIPS
    RMM: Reinforced Memory Management for Class-Incremental Learning
    Yaoyao Liu, Bernt Schiele, Qianru Sun
    Neural Information Processing Systems (NeurIPS), 2021.
    PDF Code Project Page BibTex

  8. CVPR
    Adaptive Aggregation Networks for Class-Incremental Learning
    Yaoyao Liu, Bernt Schiele, Qianru Sun
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
    PDF Code Project Page BibTex GitHub Stars

  9. CVIU
    Learning to Teach and Learn for Semi-supervised Few-shot Image Classification
    Xinzhe Li, Jianqiang Huang, Yaoyao Liu, Qin Zhou, Shibao Zheng, Bernt Schiele, Qianru Sun
    Computer Vision and Image Understanding (CVIU), Volume 212, 2021.
    PDF Code BibTex

  10. TNNLS
    Generating Face Images with Attributes for Free
    Yaoyao Liu, Qianru Sun, Xiangnan He, An-An Liu, Yuting Su, Tat-Seng Chua
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Volume 32, Number 6, 2021.
    PDF BibTex

  11. ECCV
    An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning
    Yaoyao Liu, Bernt Schiele, Qianru Sun
    European Conference on Computer Vision (ECCV), 2020.
    PDF Code Project Page BibTex

  12. CVPR
    Mnemonics Training: Multi-Class Incremental Learning without Forgetting
    Yaoyao Liu, Yuting Su, An-An Liu, Bernt Schiele, Qianru Sun
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
    PDF Code Project Page BibTex Oral Presentation

  13. NeurIPS
    Learning to Self-Train for Semi-Supervised Few-Shot Classification
    Xinzhe Li, Qianru Sun, Yaoyao Liu, Shibao Zheng, Qin Zhou, Tat-Seng Chua, Bernt Schiele
    Neural Information Processing Systems (NeurIPS), 2019.
    PDF Code Project Page BibTex

  14. CVPR
    Meta-Transfer Learning for Few-Shot Learning
    Qianru Sun*, Yaoyao Liu*, Tat-Seng Chua, Bernt Schiele
    (* Equal contribution)
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
    PDF Code Project Page BibTex
    800+ Citations • 600+ GitHub Stars • Featured in NUS News
    Top 120 Most Cited CVPR Papers over the Last Five Years

Teaching

Invited Talks

Learning from Imperfect Data: Incremental Learning and Few-shot Learning.

Meta-transfer Learning for Few-shot Learning.

Learning to Self-train for Semi-supervised Few-shot Classification.

Multi-class Incremental Learning.

Services

Organization Committee

Area Chairs

Senior Program Committee

Conference Reviewers

Journal Reviewers

Contact

Address: 3400 N. Charles St., Baltimore, MD 21218-2625
Office Location: Malone Hall 248
Email: yliu538 (at) jhu.edu
Phone: (857) 209-8688



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