FurE: Efficient Instance-Specific 3D Fur Reconstruction without Animal-Fur Datasets
Realistic and editable animal fur reconstruction from multi-view images is challenging due to fine-scale detail, self-occlusion and obfuscation, and, unlike human hair, the lack of animal-fur datasets. Fur usually covers most of an animal's body, with large inter-species and intra-species variability. We present FurE, an efficient strand-based animal fur reconstruction method that recovers a per-strand, editable groom by optimizing a root-conditioned latent field, decoded into strand geometry via a PCA-based decoder. We reconstruct a defurred animal body using local fur-thickness cues from a surface-constrained Gaussian Frosting representation together with part-based priors. We further s...
| Authors | Srinjay Sarkar, Prakhar Kaushik, Soumava Paul et al. |
|---|---|
| Primary category | cs.CV |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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