mlsanityData to 7 Oct 2026

FunRec: Reconstructing Functional 3D Scenes from Egocentric Interaction Videos

arXiv 2604.05621 ↗First posted 7 Apr 2026cs.CVcited by 7

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Abstract (arXiv)

We present FunRec, a method for reconstructing functional 3D digital twins of indoor scenes directly from egocentric RGB-D interaction videos. Unlike existing methods on articulated reconstruction, which rely on controlled setups, multi-state captures, or CAD priors, FunRec operates directly on in-the-wild human interaction sequences to recover interactable 3D scenes. It automatically discovers articulated parts, estimates their kinematic parameters, tracks their 3D motion, and reconstructs static and moving geometry in canonical space, yielding simulation-compatible meshes. Across new real and simulated benchmarks, FunRec surpasses prior work by a large margin, achieving up to +50 mIoU improvement in part segmentation, 5-10 times lower articulation and pose errors, and significantly higher reconstruction accuracy. We further demonstrate applications on URDF/USD export for simulation, hand-guided affordance mapping and robot-scene interaction.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 67 of its 83 references that are in the map. First posted on arXiv 7 Apr 2026.

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67 of 83 references.

References · 67

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38 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 7.

7 papers.