Interact3D: Compositional 3D Generation of Interactive Objects

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 differentiable Signed Distance Field (SDF)-based optimization that explicitly penalizes geometry intersections.

To reduce challenging collisions, we further deploy a closed-loop, agentic refinement strategy.

A Vision-Language Model (VLM) autonomously analyzes multi-view renderings of the composed scene, formulates targeted corrective prompts, and guides an image editing module to iteratively self-correct the generation pipeline.

Extensive experiments demonstrate that Interact3D successfully produces promising collsion-aware compositions with improved geometric fidelity and consistent spatial relationships.