[2603.14375] The Pulse of Motion: Measuring Physical Frame Rate from Visual Dynamics

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.14375 (cs) [Submitted on 15 Mar 2026 (v1), last revised 27 Mar 2026 (this version, v2)] Title:The Pulse of Motion: Measuring Physical Frame Rate from Visual Dynamics Authors:Xiangbo Gao, Mingyang Wu, Siyuan Yang, Jiongze Yu, Pardis Taghavi, Fangzhou Lin, Zhengzhong Tu View a PDF of the paper titled The Pulse of Motion: Measuring Physical Frame Rate from Visual Dynamics, by Xiangbo Gao and 6 other authors View PDF HTML (experimental) Abstract:While recent generative video models have achieved remarkable visual realism and are being explored as world models, true physical simulation requires mastering both space and time. Current models can produce visually smooth kinematics, yet they lack a reliable internal motion pulse to ground these motions in a consistent, real-world time scale. This temporal ambiguity stems from the common practice of indiscriminately training on videos with vastly different real-world speeds, forcing them into standardized frame rates. This leads to what we term chronometric hallucination: generated sequences exhibit ambiguous, unstable, and uncontrollable physical motion speeds. To address this, we propose Visual Chronometer, a predictor that recovers the Physical Frames Per Second (PhyFPS) directly from the visual dynamics of an input video. Trained via controlled temporal resampling, our method estimates the true temporal scale implied by the motion itself, bypassing unreliable ...