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Visual Physics: Discovering Physical Laws from Videos

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arxiv 1911.11893 v1 pith:5CQP2KES submitted 2019-11-27 cs.CV

Pradyumna Chari , Chinmay Talegaonkar , Yunhao Ba , Achuta Kadambi This is my paper · ORCID
classification cs.CV
keywords governinglawsmotionphysicalphysicsdiscoverelementarymachine
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we teach a machine to discover the laws of physics from video streams. We assume no prior knowledge of physics, beyond a temporal stream of bounding boxes. The problem is very difficult because a machine must learn not only a governing equation (e.g. projectile motion) but also the existence of governing parameters (e.g. velocities). We evaluate our ability to discover physical laws on videos of elementary physical phenomena, such as projectile motion or circular motion. These elementary tasks have textbook governing equations and enable ground truth verification of our approach.

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Cited by 1 Pith paper

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  1. Physics-Grounded Motion Forecasting via Equation Discovery for Trajectory-Guided Image-to-Video Generation

    cs.CV 2025-07 conditional novelty 5.0 of 10

    A retrieval-initialized symbolic regression method discovers equations of motion from video trajectories and uses them to guide image-to-video generation, improving physical alignment on classical mechanics scenes.

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