3 papers
cs.CV2025
Cross-Domain Attribute Alignment with CLIP: A Rehearsal-Free Approach for Class-Incremental Unsupervised Domain Adaptation
Kerun Mi, Guoliang Kang, Guangyu Li +3
Class-Incremental Unsupervised Domain Adaptation (CI-UDA) aims to adapt a model from a labeled source domain to an unlabeled target domain, where the sets of potential target class…
cs.CV2024
Domain adaptive pose estimation via multi-level alignment
Yugan Chen, Lin Zhao, Yalong Xu +3
Domain adaptive pose estimation aims to enable deep models trained on source domain (synthesized) datasets produce similar results on the target domain (real-world) datasets. The e…
cs.CV2024
A comprehensive framework for occluded human pose estimation
Linhao Xu, Lin Zhao, Xinxin Sun +3
Occlusion presents a significant challenge in human pose estimation. The challenges posed by occlusion can be attributed to the following factors: 1) Data: The collection and annot…