Synthetic Video Enhances Physical Fidelity in Video Synthesis
Authors: name: Qi Zhao, name: Xingyu Ni, name: Ziyu Wang, name: Feng Cheng, name: Ziyan Yang, name: Lu Jiang, name: Bohan Wang

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/