SCAPO: Self-Supervised Category-Level Articulated Pose Estimation from a Single 3D Observation 事件

SCAPO: Self-Supervised Category-Level Articulated Pose Estimation from a Single 3D Observation arXiv:2606.01940v1 Announce Type: new Abstract: Existing methods for category-level object articulation from a single 3D observation often rely on dense supervision, multi-frame inputs, or CAD templates, and still struggle to disentangle geometry from articulation or to recover explicit joint parameters. We propose SCAPO, a self-supervised framework that estimates canonical geometry, rigid part segmen