FurE: Efficient Instance-Specific 3D Fur Reconstruction without Animal-Fur Datasets

arXiv:2609.35770 · cs.CV, cs.AI, cs.GR · Submitted 2026-09-28 · Read on arXiv

cs.CV, cs.AI, cs.GR

Submitted: 2026-09-28

Updated: 2026-09-28

Project page: https://toshi2k2.github.io/fure

Terminology

• Calibration — 6× in this paper · explained in 7 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Fidelity — 4× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Latent Representation — 3× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 1× in this paper
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Gaussian Frosting: Editable Complex Radiance Fields with Real-Time Rendering
• GaussianHair: Hair Modeling and Rendering with Light-aware Gaussians
• CGHair: Compact Gaussian Hair Reconstruction with Card Clustering
• GroomGen: A High-Quality Generative Hair Model Using Hierarchical Latent Representations

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