HumanPhys: A Human-Centric Physical-World Perception Benchmark for Real-World Visual Reasoning
We introduce HumanPhys, a human-centric benchmark for real-world physical perception, and a training corpus emitted by the same pipeline. Each question targets a physically grounded quantity related to people, including depth, inter-person distance, gaze angle, displacement, velocity, heading-step trajectory, blink count, and contact-deformation strength. The rendered probes additionally test illumination inference from body and face cues and camera ego-motion, both with and without a person in the frame. All labels are derived programmatically from sensor calibration, source metadata, or renderer state, rather than written by annotators or produced by estimators on the benchmark frames. ...
| Authors | Yiming Zhang, Enzhi Zhou, Junan Lin et al. |
|---|---|
| Primary category | cs.CV |
| Published | 10 October 2026 |
| Last updated at source | 10 October 2026 |
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