2026
Beyond Binary Contrast: Modeling Continuous Skeleton Action Spaces with Transitional Anchors
CVPR 2026
Self-supervised contrastive learning has emerged as a powerful paradigm for skeleton-based action recognition by enforcing consistency in the embedding space. However, existing methods rely on binary contrastive objectives that overlook the intrinsic continuity of human motion, resulting in fragment