TORA: Topological Representation Alignment for 3D Shape Assembly
Flow-matching methods for 3D shape assembly learn point-wise velocity fields that transport parts toward assembled configurations, yet they receive no explicit guidance about which cross-part interactions should drive the motion. We introduce TORA, a topology-first representation alignment framework that distills relational structure from a frozen pretrained 3D encoder into the flow-matching backbone during training. We first realize this via simple instantiation, token-wise cosine matching, which injects the learned geometric descriptors from the teacher representation. We then extend to employ a Centered Kernel Alignment (CKA) loss to match the similarity structure between student and t...
| Authors | Nahyuk Lee, Zhiang Chen, Marc Pollefeys et al. |
|---|---|
| Primary category | cs.CV |
| Published | 5 April 2026 |
| Last updated at source | 30 June 2026 |
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