RigidBench: Evaluating Rigid-Body Physics in Video Generation Models
Video models are increasingly used to predict what happens next in a scene, yet the metrics commonly used to compare their outputs say little about whether the predicted objects move correctly. Motion, geometry, identity, background stability, and visual similarity can fail independently, but whole-frame scores often mix these errors together. We introduce RigidBench, a simulator-grounded benchmark that compares a generated continuation with a reference rollout from the same initial frame and motion description. Its five rigid-body tasks vary objects, materials, viewpoints, and indoor and outdoor scenes, with per-frame masks, depth, 6-DoF trajectories, and contacts available for scoring. ...
| Authors | Swarnim Jain, Shangzhe Wu |
|---|---|
| Primary category | cs.CV |
| Published | 16 August 2026 |
| Last updated at source | 16 August 2026 |
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