Structure from Collision

• URL: http://arxiv.org/abs/2505.21335v1
• Date: Tue, 27 May 2025 15:30:01 GMT
• Title: Structure from Collision
• Abstract summary: A new task called Structure from Collision (SfC) aims to estimate the structure (including the invisible internal structure) of an object from appearance changes during collision.<n>We propose a novel model called SfC-NeRF that optimize the invisible internal structure of an object through a video sequence under physical, appearance (i.e., visible external structure) and neural constraints.<n>Experiments on 115 objects involving diverse structures revealed the properties of SfC and demonstrated the effectiveness of the proposed SfC-NeRF.
• Score: 20.586692311724914
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent advancements in neural 3D representations, such as neural radiance fields (NeRF) and 3D Gaussian splatting (3DGS), have enabled the accurate estimation of 3D structures from multiview images. However, this capability is limited to estimating the visible external structure, and identifying the invisible internal structure hidden behind the surface is difficult. To overcome this limitation, we address a new task called Structure from Collision (SfC), which aims to estimate the structure (including the invisible internal structure) of an object from appearance changes during collision. To solve this problem, we propose a novel model called SfC-NeRF that optimizes the invisible internal structure of an object through a video sequence under physical, appearance (i.e., visible external structure)-preserving, and keyframe constraints. In particular, to avoid falling into undesirable local optima owing to its ill-posed nature, we propose volume annealing; that is, searching for global optima by repeatedly reducing and expanding the volume. Extensive experiments on 115 objects involving diverse structures (i.e., various cavity shapes, locations, and sizes) and material properties revealed the properties of SfC and demonstrated the effectiveness of the proposed SfC-NeRF.

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