PhySGA: A Physics-Space Grounded Agentic Framework for Generalizable and Interactive 3D Composition
[Sztuczna inteligencja] Autorzy: Weichen Lyu, Chong Xia, Mingyu Dong i 3 więcej
3D object composition is pivotal to digital content creation and robot simulation, while also serving as a critical testbed for physical intelligence in foundation models. Previous methods either leverage large language models to directly predict object coordinates, or utilize generative diffusion priors to synthesize composite images for visual alignment, both of which rely on static priors in digital spaces. However, these methods consistently struggle with complex compositions such as precise hanging, gravity-driven settling and hidden containment, as these tasks require interactive construction processes involving global planning, fine-grained alignment, and physical simulation. To address these challenges, we propose PhySGA, a Physics-Space Grounded Agentic Framework for 3D composition via agent exploration and physical simulation, enabling the universal interactive assembly of rig…
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja