Point Diffusion Mamba: Unified Diffusion-State-Space Modeling for Single-View 3D Reconstruction under Data Scarcity

arXiv:2609.25538 · cs.CV · Submitted 2026-09-22 · Read on arXiv

cs.CV

Submitted: 2026-09-22

Updated: 2026-09-22

Code: https://github.com/NWUzhouwei/PDM

Terminology

• Diffusion Model — 17× in this paper · explained in 8 episodes
• Point Diffusion Mamba — 13× in this paper
• Diffusion Models — 12× in this paper · explained in 6 episodes
• Transformer — 11× in this paper · explained in 2 episodes
• Point Clouds — 10× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 9× in this paper
• Ablation — 6× in this paper · explained in 1 episode
• Dynamic Weighted Sampling — 6× in this paper
• State-Space Model — 6× in this paper
• Aggregation — 5× in this paper · explained in 1 episode
• Consistency — 5× in this paper · explained in 3 episodes
• Generative Model — 4× in this paper · explained in 2 episodes
• alpha — 4× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 3× in this paper
• Core — 3× in this paper · explained in 2 episodes
• F1 Score — 3× in this paper · explained in 3 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Local Geometric Aggregation — 3× in this paper
• Accuracy — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Chamfer Distance — 1× in this paper
• Clustering — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Gaussian Splatting — 1× in this paper · explained in 4 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Mode Collapse — 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
• Semantic Gap — 1× in this paper · explained in 2 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• ShapeNet: An Information-Rich 3D Model Repository
• CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• Efficiently Modeling Long Sequences with Structured State Spaces

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