Interact3D: Compositional 3D Generation of Interactive Objects
Hui Shan, Keyang Luo, Ming Li, Sizhe Zheng, Yanwei Fu, Zhen Chen, Xiangru Huang

TL;DR
Interact3D introduces a novel framework for generating physically plausible, collision-aware 3D composite objects from single images, effectively preserving spatial relationships and geometric details through a multi-stage, refinement-driven process.
Contribution
The paper presents a new two-stage composition pipeline with a VLM-guided refinement strategy for 3D object composition, addressing occlusion and spatial relationship preservation challenges.
Findings
Produces collision-aware, high-fidelity 3D compositions
Improves geometric detail preservation in occluded regions
Demonstrates effective spatial relationship maintenance
Abstract
Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional objects from single images--particularly under occlusions--remains challenging. Existing methods often degrade geometric details in hidden regions and fail to preserve the underlying object-object spatial relationships (OOR). We present a novel framework Interact3D designed to generate physically plausible interacting 3D compositional objects. Our approach first leverages advanced generative priors to curate high-quality individual assets with a unified 3D guidance scene. To physically compose these assets, we then introduce a robust two-stage composition pipeline. Based on the 3D guidance scene, the primary object is anchored through precise global-to-local geometric alignment (registration), while subsequent geometries are integrated using a…
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Taxonomy
Topics3D Shape Modeling and Analysis · Generative Adversarial Networks and Image Synthesis · Computer Graphics and Visualization Techniques
