arXiv:2606. 28128v1 Announce Type: cross Abstract: Video generation models have emerged as a promising paradigm for embodied world simulation.
By Peiwen Zhang, Yufan Deng, Shangkun Sun, Juncheng Ma, Duomin Wang, Jonas Du, Zilin Pan, Ye Huang, Hao Liang, Songyan Huang, Ruihua Zhang, Enze Xie, Ming-Yu Liu, Daquan Zhou
Recent advances in image-to-video generation have improved visual realism, making physically grounded and controllable dynamics an important step toward future world simulation. Current models often generate plausible motion, but it is not reliably governed by explicit physical causes, and instance-level constraints can leak or become entangled in multi-object interactions.
arXiv:2609.13006v2 Announce Type: replace
Abstract: Video diffusion models (VDMs) synthesize photorealistic content, yet they often fail to follow the course that a physical phenomenon should take wi...
By Minh-Loi Nguyen, Xuan-Vu Le, Trung-Nghia Le, Tam V. Nguyen, Minh-Triet Tran, Thanh-Toan Do
arXiv:2601.07823v2 Announce Type: cross
Abstract: Video world models have emerged as promising candidates for high-fidelity world models, offering the potential to synthesize high-quality videos capt...
By Zhiting Mei, Tenny Yin, Ola Shorinwa, Apurva Badithela, Zhonghe Zheng, Joseph Bruno, Madison Bland, Lihan Zha, Asher Hancock, Jaime Fern\'andez Fisac, Philip Dames, Anirudha Majumdar
Fluid-Gen-Zero is a training-free framework that generates physics-aware fluid-object interaction videos by separating physical reasoning from appearance synthesis. It uses a physics simulator for motion dynamics and a pretrained video generator for visual quality, coordinated through a two-level agentic workflow involving a vision-language model for planning and latent-space guidance for simulation signals. The method improves simulation alignment and fluid flow accuracy across multiple backbones while maintaining perceptual quality, as shown by quantitative metrics and human preference studies.
By Hong Huang, Yuqiu Liu, Chenyu You, Daniel Martin, Chuhang Zou, Wuyang Chen
We present Fluid-Gen-Zero, a training-free framework for physics-aware fluid-object interaction video generation that decouples physical reasoning from appearance synthesis. Our key insight is to dele...