Summary of Physdreamer: Physics-based Interaction with 3d Objects Via Video Generation, by Tianyuan Zhang et al.
PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generation
by Tianyuan Zhang, Hong-Xing Yu, Rundi Wu, Brandon Y. Feng, Changxi Zheng, Noah Snavely, Jiajun Wu, William T. Freeman
First submitted to arxiv on: 19 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this paper, the authors introduce PhysDreamer, a physics-based approach that enables static 3D objects to dynamically respond to interactive stimuli in a physically plausible manner. The method leverages object dynamics priors learned by video generation models and distills these priors to synthesize realistic object responses to novel interactions. The authors demonstrate their approach on diverse examples of elastic objects and evaluate the realism of the synthesized interactions through a user study. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Realistic virtual experiences require 3D objects that can interact realistically with users. To achieve this, PhysDreamer uses physics-based approaches to simulate how real-world objects behave when interacting with forces or agents. The method learns object dynamics priors from video generation models and applies them to static 3D objects, making them seem more realistic. This paper shows the potential of PhysDreamer by applying it to different elastic objects and getting feedback from users. |
