PoseBridge: Bridging the Skeletonization Gap for Zero-Shot Skeleton-Based Action Recognition
Zero-shot skeleton-based action recognition (ZSSAR) is typically treated as a skeleton-text alignment problem: encode joint-coordinate sequences, align them with language, and classify unseen actions. We argue that this alignment is often too late. Skeletons are not complete action observations, but compressed outputs of human pose estimation (HPE); by the time alignment begins, human-object interactions and pose-relative visual cues may no longer be explicit. We call this upstream semantic loss. To address it, we propose PoseBridge, an HPE-aware ZSSAR framework that bridges intermediate HPE representations to skeleton-text alignment. Rather than adding an RGB action branch or object dete...
| Authors | Sanghyeon Lee, Jinwoo Kim, Jong Taek Lee |
|---|---|
| Primary category | cs.CV |
| Published | 12 May 2026 |
| Last updated at source | 28 September 2026 |
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