REACT3D: Recovering Articulations for Interactive Physical 3D Scenes

• URL: http://arxiv.org/abs/2510.11340v2
• Date: Tue, 14 Oct 2025 09:16:39 GMT
• Title: REACT3D: Recovering Articulations for Interactive Physical 3D Scenes
• Authors: Zhao Huang, Boyang Sun, Alexandros Delitzas, Jiaqi Chen, Marc Pollefeys,
• Abstract summary: REACT3D is a framework that converts static 3D scenes into simulation-ready interactive replicas with consistent geometry.<n>We achieve state-of-the-art performance on detection/segmentation and articulation metrics across diverse indoor scenes.
• Score: 96.27769519526426
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Interactive 3D scenes are increasingly vital for embodied intelligence, yet existing datasets remain limited due to the labor-intensive process of annotating part segmentation, kinematic types, and motion trajectories. We present REACT3D, a scalable zero-shot framework that converts static 3D scenes into simulation-ready interactive replicas with consistent geometry, enabling direct use in diverse downstream tasks. Our contributions include: (i) openable-object detection and segmentation to extract candidate movable parts from static scenes, (ii) articulation estimation that infers joint types and motion parameters, (iii) hidden-geometry completion followed by interactive object assembly, and (iv) interactive scene integration in widely supported formats to ensure compatibility with standard simulation platforms. We achieve state-of-the-art performance on detection/segmentation and articulation metrics across diverse indoor scenes, demonstrating the effectiveness of our framework and providing a practical foundation for scalable interactive scene generation, thereby lowering the barrier to large-scale research on articulated scene understanding. Our project page is https://react3d.github.io/

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