mlsanityData to 13 Oct 2026

Synthetic Video Enhances Physical Fidelity in Video Synthesis

arXiv 2503.20822 ↗First posted 26 Mar 2025eess.IV cs.AI cs.GRcited by 15

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Abstract (arXiv)

We investigate how to enhance the physical fidelity of video generation models by leveraging synthetic videos derived from computer graphics pipelines. These rendered videos respect real-world physics, such as maintaining 3D consistency, and serve as a valuable resource that can potentially improve video generation models. To harness this potential, we propose a solution that curates and integrates synthetic data while introducing a method to transfer its physical realism to the model, significantly reducing unwanted artifacts. Through experiments on three representative tasks emphasizing physical consistency, we demonstrate its efficacy in enhancing physical fidelity. While our model still lacks a deep understanding of physics, our work offers one of the first empirical demonstrations that synthetic video enhances physical fidelity in video synthesis. Website: https://kevinz8866.github.io/simulation/

Key facts. Cited by 15 papers in the map (data through 13 Oct 2026). Builds on 54 of its 78 references that are in the map. First posted on arXiv 26 Mar 2025.

Builds on

54 of 78 references.

References · 54

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38 more
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Citing papers per year: 2025: 8; 2026: 7.

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