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Yu Tian

Yu Tian is a postdoctoral research fellow at Harvard University. He received his Ph.D. in computer science at the Australian Institute for Machine Learning (AIML), University of Adelaide. Previously, Dr. Tian obtained his bachelor’s degree in computer science with First Class Honours at the University of Adelaide.

Research

My main research interests are in the fields of computer vision and medical image analysis, in particular abnormality and rarity learning tasks, such as image/video anomaly detection for surveillance and industrial applications or early detection of diseases.

News

Aug, 2023 One paper about medical anomaly detection is accepted in MICCAI-MLMI.
Jul, 2023 4 papers are accepted in ICCV 2023.
Jul, 2023 One paper about artifact correction is accepted in IEEE Journal of Biomedical and Health Informatics (JBHI).
Jul, 2023 One paper about medical anomaly detection is accepted in Medical Image Analysis.
Mar, 2023 Call for Participation for our CVPR 2023 tutorial on Recent Advances in Anomaly Detection.
Mar, 2023 One ARVO Imaging abstract is selected as oral presentation.

Selected Publications

* denotes equal contribution; ^ denotes corresponding authorship.

  1. FairSeg: A Large-scale Medical Image Segmentation Dataset for Fairness Learning with Fair Error-Bound Scaling
    Yu Tian*, Yan Luo*, Min Shi*, Ava Kouhana, Tobias Elze, and Mengyu Wang
    arXiv preprint , 2023
    PDF Code Dataset
  2. Harvard Eye Fairness: A Large-Scale 3D Imaging Dataset for Equitable Eye Diseases Screening and Fair Identity Scaling
    Yan Luo*, Yu Tian*, Min Shi*, Tobias Elze, and Mengyu Wang
    arXiv preprint , 2023
    PDF Code Dataset
  3. Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization
    Yan Luo*, Yu Tian*, Min Shi*, Tobias Elze, and Mengyu Wang
    arXiv preprint , 2023
    PDF Code Dataset
  4. AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection
    Qihang Zhou, Guansong Pang, Yu Tian, Shibo He, and Jiming Chen
    arXiv preprint , 2023
    PDF Code
  5. UnifiedVisionGPT: Streamlining Vision-Oriented AI through Generalized Multimodal Framework
    Chris Kelly, Luhui Hu, Cindy Yang, Yu Tian, Deshun Yang, Bang Yang, Zaoshan Huang, Zihao Li, and Yuexian Zou
    arXiv preprint arXiv:2310.12790 , 2023
    PDF Code
  6. Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection
    Jiawen Zhu, Choubo Ding, Yu Tian, and Guansong Pang
    arXiv preprint arXiv:2310.12790 , 2023
    PDF Code
  7. Harvard Glaucoma Detection and Progression: A Multimodal Multitask Dataset and Generalization-Reinforced Semi-Supervised Learning
    Yan Luo*, Min Shi*, Yu Tian*, Tobias Elze, and Mengyu Wang
    In Proceedings of the IEEE/CVF international conference on computer vision (ICCV), 2023
    PDF Code Dataset
  8. Self-supervised Pseudo Multi-class Pre-training for Unsupervised Anomaly Detection and Segmentation in Medical Images
    Yu Tian*, Fengbei Liu*, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W Verjans, Rajvinder Singh, and Gustavo Carneiro
    Medical Image Analysis (MedIA), 2023
    PDF Code
  9. Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes
    Yu Tian*, Yuyuan Liu*, Guansong Pang, Fengbei Liu, Yuanhong Chen, and Gustavo Carneiro
    European Conference on Computer Vision (ECCV Oral), 2022
    PDF Code
  10. Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection
    Yu Tian, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan W Verjans, and Gustavo Carneiro
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI Early Accept), 2022
    PDF Code
  11. ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification
    Fengbei Liu*, Yu Tian*, Yuanhong Chen, Yuyuan Liu, Vasileios Belagiannis, and Gustavo Carneiro
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
    PDF Code
  12. Deep One-Class Classification via Interpolated Gaussian Descriptor
    Yuanhong Chen*, Yu Tian*^, Guansong Pang, and Gustavo Carneiro
    In Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI Oral), 2022
    PDF Code
  13. Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning
    Yu Tian, Guansong Pang, Yuanhong Chen, Rajvinder Singh, Johan W Verjans, and Gustavo Carneiro
    In Proceedings of the IEEE/CVF international conference on computer vision (ICCV), 2021
    PDF Code
  14. Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images
    Yu Tian, Guansong Pang, Fengbei Liu, Seon Ho Shin, Johan W Verjans, Rajvinder Singh, Gustavo Carneiro, and  others
    In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021
    PDF Code
  15. Few-shot anomaly detection for polyp frames from colonoscopy
    Yu Tian, Gabriel Maicas, Leonardo Zorron Cheng Tao Pu, Rajvinder Singh, Johan W Verjans, and Gustavo Carneiro
    In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020
    PDF Code