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Paper · arXiv 2605.05163

PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World

Yunhan Yang, Chunshi Wang, Junliang Ye, Yang Li, Zanxin Chen, Zehuan Huang, Yao Mu, Zhuo Chen, Chunchao Guo, Xihui Liu

38 upvotesMay 6, 2026arXiv 预印本
AI 摘要

PhysForge generates interactive 3D assets by combining visual-language modeling for physical planning with a physics-grounded diffusion model that synthesizes detailed geometry and kinematic parameters through a novel injection mechanism.

visual-language modelphysics-grounded diffusion modelKineVoxel InjectionHierarchical Physical Blueprintkinematic parameterssimulation-ready assets

Abstract

Synthesizing physics-grounded 3D assets is a critical bottleneck for interactive virtual worlds and embodied AI. Existing methods predominantly focus on static geometry, overlooking the functional properties essential for interaction. We propose that interactive asset generation must be rooted in functional logic and hierarchical physics. To bridge this gap, we introduce PhysForge, a decoupled two-stage framework supported by PhysDB, a large-scale dataset of 150,000 assets with four-tier physical annotations. First, a VLM acts as a "physical architect" to plan a "Hierarchical Physical Blueprint" defining material, functional, and kinematic constraints. Second, a physics-grounded diffusion model realizes this blueprint by synthesizing high-fidelity geometry alongside precise kinematic parameters via a novel KineVoxel Injection (KVI) mechanism. Experiments demonstrate that PhysForge produces functionally plausible, simulation-ready assets, providing a robust data engine for interactive 3D content and embodied agents.

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