15 citations · 20 across the 6 of their papers we have counts for
6 papers
Imbalance-Agnostic Source-Free Domain Adaptation via Avatar Prototype Alignment
Hongbin Lin, Mingkui Tan, Yifan Zhang +5
Source-free Unsupervised Domain Adaptation (SF-UDA) aims to adapt a well-trained source model to an unlabeled target domain without access to the source data. One key challenge is…
Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation
Hongbin Lin, Yifan Zhang, Zhen Qiu +4
This paper studies a new, practical but challenging problem, called Class-Incremental Unsupervised Domain Adaptation (CI-UDA), where the labeled source domain contains all classes,…
Improved Knowledge Distillation via Adversarial Collaboration
Zhiqiang Liu, Chengkai Huang, Yanxia Liu
Knowledge distillation has become an important approach to obtain a compact yet effective model. To achieve this goal, a small student model is trained to exploit the knowledge of…
Semi-Online Knowledge Distillation
Zhiqiang Liu, Yanxia Liu, Chengkai Huang
Knowledge distillation is an effective and stable method for model compression via knowledge transfer. Conventional knowledge distillation (KD) is to transfer knowledge from a larg…
Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation
Zhen Qiu, Yifan Zhang, Hongbin Lin +4
We study a practical domain adaptation task, called source-free unsupervised domain adaptation (UDA) problem, in which we cannot access source domain data due to data privacy issue…
Retinal Image Segmentation with a Structure-Texture Demixing Network
Shihao Zhang, Huazhu Fu, Yanwu Xu +2
Retinal image segmentation plays an important role in automatic disease diagnosis. This task is very challenging because the complex structure and texture information are mixed in…