DinoComplete: 3D Shape Completion with Distilled Semantic Priors and State Space Models

arXiv:2605.26949 · cs.CV, cs.GR · Submitted 2026-05-26 · Read on arXiv

cs.CV, cs.GR

Submitted: 2026-05-26

Updated: 2026-09-21

Code: https://github.com/yinyunie/depth_renderer

Terminology

• Distillation — 13× in this paper · explained in 2 episodes
• Generalization — 10× in this paper · explained in 13 episodes
• State Space Models — 8× in this paper
• Transformer — 8× in this paper · explained in 2 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Aggregation — 5× in this paper · explained in 1 episode
• Foundation Model — 5× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 4× in this paper
• Foundation Models — 4× in this paper · explained in 7 episodes
• Multi-Scale Voxel Mamba — 4× in this paper
• Robustness — 4× in this paper · explained in 5 episodes
• ACM Transactions on Graphics — 3× in this paper
• Ablation — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Point Clouds — 3× in this paper · explained in 2 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• State Space Models (SSMs) — 2× in this paper · explained in 4 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Self-distillation — 1× in this paper · explained in 6 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• Layer Normalization
• ShapeNet: An Information-Rich 3D Model Repository
• SC-Diff: 3D Shape Completion with Latent Diffusion Models
• DINOv3

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