no code implementations • 4 Sep 2023 • Yiwen Cao, Yukun Su, Wenjun Wang, Yanxia Liu, Qingyao Wu
Weakly supervised object localization (WSOL) strives to learn to localize objects with only image-level supervision.
no code implementations • 22 May 2023 • Hongbin Lin, Mingkui Tan, Yifan Zhang, Zhen Qiu, Shuaicheng Niu, Dong Liu, Qing Du, Yanxia Liu
To address this issue, we study a more practical SF-UDA task, termed imbalance-agnostic SF-UDA, where the class distributions of both the unseen source domain and unlabeled target domain are unknown and could be arbitrarily skewed.
1 code implementation • 22 Jul 2022 • Hongbin Lin, Yifan Zhang, Zhen Qiu, Shuaicheng Niu, Chuang Gan, Yanxia Liu, Mingkui Tan
2) Prototype-based alignment and replay: based on the identified label prototypes, we align both domains and enforce the model to retain previous knowledge.
no code implementations • 29 Nov 2021 • Zhiqiang Liu, Chengkai Huang, Yanxia Liu
To achieve this goal, a small student model is trained to exploit the knowledge of a large well-trained teacher model.
1 code implementation • 23 Nov 2021 • Zhiqiang Liu, Yanxia Liu, Chengkai Huang
However, to the best of our knowledge, KD and DML have never been jointly explored in a unified framework to solve the knowledge distillation problem.
1 code implementation • 18 Jun 2021 • Zhen Qiu, Yifan Zhang, Hongbin Lin, Shuaicheng Niu, Yanxia Liu, Qing Du, Mingkui Tan
(2) prototype adaptation: based on the generated source prototypes and target pseudo labels, we develop a new robust contrastive prototype adaptation strategy to align each pseudo-labeled target data to the corresponding source prototypes.
Ranked #13 on Domain Adaptation on Office-31
no code implementations • 15 Jul 2020 • Shihao Zhang, Huazhu Fu, Yanwu Xu, Yanxia Liu, Mingkui Tan
Retinal image segmentation plays an important role in automatic disease diagnosis.