AI RESEARCH
DailyArt: Discovering Articulation from Single Static Images via Latent Dynamics
arXiv CS.CV
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ArXi:2604.07758v1 Announce Type: new Articulated objects are essential for embodied AI and world models, yet inferring their kinematics from a single closed-state image remains challenging because crucial motion cues are often occluded. Existing methods either require multi-state observations or rely on explicit part priors, retrieval, or other auxiliary inputs that partially expose the structure to be inferred. In this work, we present DailyArt, which formulates articulated joint estimation from a single static image as a synthesis-mediated reasoning problem.