PhyScene3D: Physically Consistent Interactive 3D Tabletop Scene Generation 文章

ArXiv CS.CV2026-06-02NEWSen作者: Weixing Chen, Zhuoqian Feng, Yang Liu, Yexin Zhang, Yifan Wen, Yinghong Liao, Weichao Qiu, Guanbin Li, Liang Lin

摘要

arXiv:2606.01649v1 Announce Type: new Abstract: Generating physically consistent 3D tabletop scenes is a fundamental yet underexplored problem for interactive and generalist robotic learning. The challenge stems from dense object hierarchies and irregular affordances. Here, an interactive scene denotes a physically valid, collision-free environment directly loadable into physics simulators. Existing methods, ranging from decoupled symbolic solvers to end-to-end regression models, often suffer from error propagation or overfitting to noisy supervision containing widespread physical violations. To address these limitations, we introduce PhyScene3D, a framework that reformulates generation as a Human-Mimetic Constructive Process. The proposed Cognitive Topological Reasoning Chain (CTRC) factorizes scene synthesis into a sequential, anchor-conditioned process. It employs a 3D AABB-based placement scheme that imposes a strong structural inductive bias.