Motion is Structure: ZORA for Zero-Shot 3D Rigging from In-the-Wild 4D Dynamics

Automating the creation of articulated 3D characters is a longstanding challenge in computer graphics and embodied AI, with applications that span gaming, visual effects, and physical simulation. Recent advances in monocular 4D reconstruction enable extraction of dynamic 3D surfaces from an input single-view video, yet these outputs remain baked geometry: temporally re-playable but not editable or animatable. Converting them into articulated assets with explicit skeletons and skinning weights is a critical unsolved step. Existing automatic rigging methods rely on rig-label supervision or category-specific priors, making them brittle under severe self-contact and out-of-distribution topologies such as multi-limbed creatures or non-humanoid figures. We introduce **ZORA** (Zero-shot Optimization for Rigging Assets), a training-free framework built on a single principle: motion is structure. Given a reconstructed 4D surface, ZORA extracts a topology-aware kinematic scaffold by routing geodesic paths through regions of high temporal motion variance, suppressing spurious shortcuts at self-contact without any learned prior. It then recovers an explicit linear blend skinning rig via joint optimization of skinning weights and per-frame rigid transformations under four complementary objectives: motion affinity, topological locality, temporal smoothness, and volumetric consistency. Crucially, no template skeleton or labeled training data is required, coherent 4D motion alone serves as a geometric prior, binding vertices with correlated dynamics to the same articulated part. ZORA produces editable, production-ready rigs across a diverse range of characters, including those with complex topologies where prior methods degrade.