The proposed Skeleton-Aware SAM2 improves both overlap-based and topology-aware performance over strong baselines and topology-aware loss variants and suggests that explicit morphology-guided conditioning provides useful structural bias for topology-sensitive angiographic vessel segmentation under domain shifts.
Shuang Liang, Chun-Yi Yang, Zhicheng Liu et al.· Pattern Analysis and Applica...· 0 citations
Auxiliary visual and language modalities can improve self-supervised skeleton action representation learning by supplying object, scene, and semantic cues that joint coordinates lack. Existing cross-modal training signals are often defined at the sample level or aligned in a single global space, making them sensitive t...
Kenan Ye, Shengjie Zhao, Shuang Liang· IEEE International Conferenc...· 0 citations
Results show that prototype-mediated vision-language transfer can improve skeleton representations for the behavior-interpretation stage of positioning and tracking pipelines, and CrossVLS is proposed, which is a cross-modal vision-language-guided framework that transfers semantic knowledge from red, green, and blue fr...
Kenan Ye, Shengjie Zhao, Shuang Liang· Electronics· 0 citations
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