VGGT-Diff: Visual Geometry Meets Diffusion for Sparse-View Novel View Synthesis

arXiv:2609.33253 · cs.CV, cs.AI · Submitted 2026-09-27 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-27

Updated: 2026-09-27

Code: https://github.com/chenkangjie1123/VGGT-Diff

Terminology

• Consistency — 19× in this paper · explained in 3 episodes
• Diffusion Model — 17× in this paper · explained in 8 episodes
• Conference on Computer Vision and Pattern Recognition — 12× in this paper
• Diffusion Models — 12× in this paper · explained in 6 episodes
• Regularization — 11× in this paper · explained in 3 episodes
• Robustness — 10× in this paper · explained in 5 episodes
• Adaptation — 8× in this paper · explained in 1 episode
• Alignment — 7× in this paper · explained in 1 episode
• Fidelity — 7× in this paper · explained in 2 episodes
• Gaussian Splatting — 7× in this paper · explained in 4 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Visual Geometry Router — 6× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 5× in this paper
• Point-Track Residual Consistency — 5× in this paper
• 3D Gaussian Splatting — 4× in this paper · explained in 2 episodes
• Flow Matching — 4× in this paper · explained in 8 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Latent Space — 3× in this paper · explained in 7 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Point Clouds — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• LoRA Adaptation — 1× in this paper · explained in 2 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
• LVSM: A Large View Synthesis Model with Minimal 3D Inductive Bias
• GeoNVS: Geometry Grounded Video Diffusion for Novel View Synthesis
• Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model
• AnyView: Synthesizing Any Novel View in Dynamic Scenes
• Wan: Open and Advanced Large-Scale Video Generative Models
• VGGT-$\Omega$
• Is Attention All That NeRF Needs?
• Novel View Synthesis with Diffusion Models
• Novel View Synthesis as Video Completion
• From Rays to Projections: Better Inputs for Feed-Forward View Synthesis
• ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis
• UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models

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