Publications

* denotes equal contribution; ^ denotes corresponding authorship.

Preprint

  1. arXiv
    Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder
    Yu Tian, Guansong Pang, Yuyuan Liu, Chong Wang, Yuanhong Chen, Fengbei Liu, Rajvinder Singh, Johan W Verjans, and Gustavo Carneiro
    arXiv preprint 2022
  2. arXiv
    Translation Consistent Semi-supervised Segmentation for 3D Medical Images
    Yuyuan Liu, Yu Tian, Chong Wang, Yuanhong Chen, Fengbei Liu, Vasileios Belagiannis, and Gustavo Carneiro
    arXiv preprint 2022
  3. arXiv
    Semantic-guided Image Virtual Attribute Learning for Noisy Multi-label Chest X-ray Classification
    Yuanhong Chen*, Fengbei Liu*, Yu Tian, Yuyuan Liu, and Gustavo Carneiro
    arXiv preprint arXiv:2203.01937 2022
  4. arXiv
    Self-supervised 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
    arXiv preprint 2022

Conference Papers

2022

  1. ECCV’22 Oral
    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
  2. MICCAI’22
    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
  3. MICCAI’22
    NVUM: Non-Volatile Unbiased Memory for Robust Medical Image Classification
    Fengbei Liu, Yuanhong Chen, Yu Tian, Yuyuan Liu, Chong Wang, Vasileios Belagiannis, and Gustavo Carneiro
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI Early Accept), 2022
  4. MICCAI’22
    Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation
    Yuanhong Chen, Wang Hu, Chong Wang, Yu Tian, Fengbei Liu, Yuyuan Liu, Michael Elliott, Davis McCarthy, Helen Frazer, and Gustavo Carneiro
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI Early Accept), 2022
  5. MICCAI’22
    Knowledge Distillation to Ensemble Global and Interpretable Prototype-based Mammogram Classification Models
    Chong Wang, Yuanhong Chen, Yuyuan Liu, Yu Tian, Fengbei Liu, Davis McCarthy, Michael Elliott, Helen Frazer, and Gustavo Carneiro
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI Early Accept), 2022
  6. CVPR’22
    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
  7. CVPR’22
    Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation
    Yuyuan Liu, Yu Tian, Yuanhong Chen, Fengbei Liu, Vasileios Belagiannis, and Gustavo Carneiro
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
  8. AAAI’22 Oral
    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

2021

  1. ICCV’21
    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
  2. MICCAI’21
    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
  3. MICCAI’21
    Self-supervised Mean Teacher for Semi-supervised Chest X-ray Classification
    Fengbei Liu*, Yu Tian*, Filipe R Cordeiro, Vasileios Belagiannis, Ian Reid, and Gustavo Carneiro
    In International Workshop on Machine Learning in Medical Imaging (MICCAI-MLMI), 2021

2020

  1. MICCAI’20
    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
  2. ISBI’20
    Photoshopping colonoscopy video frames
    Yuyuan Liu*, Yu Tian*^, Gabriel Maicas, Leonardo Zorron Cheng Tao Pu, Rajvinder Singh, Johan W Verjans, and Gustavo Carneiro
    In IEEE 17th International Symposium on Biomedical Imaging (ISBI), 2020

2019

  1. ISBI’19
    One-stage five-class polyp detection and classification
    Yu Tian, Leonardo ZCT Pu, Rajvinder Singh, Alastair D Burt, and Gustavo Carneiro
    In IEEE 16th International Symposium on Biomedical Imaging (ISBI), 2019

Journal Papers

2020

  1. GIE
    Computer-aided diagnosis for characterization of colorectal lesions: comprehensive software that includes differentiation of serrated lesions
    Leonardo Zorron Cheng Tao Pu, Gabriel Maicas, Yu Tian, Takeshi Yamamura, Masanao Nakamura, Hiroto Suzuki, Gurfarmaan Singh, Khizar Rana, Yoshiki Hirooka, Alastair D Burt, and others
    Gastrointestinal endoscopy (GIE), 2020

2019

  1. JGH
    Prospective study assessing a comprehensive computer-aided diagnosis for characterization of colorectal lesions: results from different centers and imaging technologies
    Leonardo Zorron Cheng Tao Pu, Gabriel Maicas, Yu Tian, Takeshi Yamamura, Gurfarmaan Singh, Khizar Rana, Hiroto Suzuki, Masanao Nakamura, Yoshiki Hirooka, and others
    Journal of Gastroenterology and Hepatology, 2019

Book Chapters

  1. Book
    Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning
    Yu Tian, Leonardo Zorron Cheng Tao Pu, Yuyuan Liu, Gabriel Maicas, Johan W Verjans, Alastair D Burt, Seon Ho Shin, Rajvinder Singh, and Gustavo Carneiro
    Deep Learning for Medical Image Analysis (second edition), 2021