Surflo: Consistent 3D Surface Flow Model with Global State
Geometry is invariant to viewpoint, which makes any collection of images a redundant encoding of a single 3D state. Existing feed-forward reconstruction models fail to exploit this: per-view methods emit overlapping, unaligned pointmaps that grow linearly with input count, while global-latent methods commit to a fixed, low-resolution output. We introduce Surflo, which compresses a variable number of unposed RGB views into K latent tokens-one global state-and decodes oriented 3D surface points by independently transporting them from noise onto the surface via flow matching. This frees the output from any fixed grid or token budget: the same latent yields from a few thousand to a million po...
| Authors | Antoine Guédon, Shu Nakamura, Nicolas Dufour et al. |
|---|---|
| Primary category | cs.CV |
| Published | 11 June 2026 |
| Last updated at source | 11 June 2026 |
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- AntoineGuedon/Surflo-eval-dataDataset · cited by
- AntoineGuedon/DL3DV-10K-MeshedDataset · cited by
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