HierGF: Hierarchical Gaussian Fields via Geometry-perception Message Passing for Sparse-view 3D Reconstruction

arXiv:2610.01056 · cs.CV, eess.IV · Submitted 2026-10-01 · Read on arXiv

cs.CV, eess.IV

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• Gaussian Splatting — 16× in this paper · explained in 4 episodes
• Consistency — 15× in this paper · explained in 3 episodes
• Ablation — 14× in this paper · explained in 1 episode
• Adaptation — 13× in this paper · explained in 1 episode
• Benchmark — 11× in this paper · explained in 2 episodes
• Regularization — 11× in this paper · explained in 3 episodes
• 3D Gaussian Splatting — 10× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 10× in this paper
• Ablation study — 8× in this paper · explained in 1 episode
• LoRA Adaptation — 8× in this paper · explained in 2 episodes
• Diffusion Model — 5× in this paper · explained in 8 episodes
• Diffusion Models — 5× in this paper · explained in 6 episodes
• Loss Function — 4× in this paper · explained in 2 episodes
• Adaptive Density Control — 3× in this paper
• Alignment — 3× in this paper · explained in 1 episode
• 3D Gaussian Splatting (3DGS) — 2× in this paper · explained in 4 episodes
• ACM Transactions on Graphics — 2× in this paper
• Distillation — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Grounding — 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 Adapters — 1× in this paper · explained in 3 episodes
• Multi-view Stereo — 1× in this paper
• Point Clouds — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• Geometry and Perception Guided Gaussians for Multiview-consistent 3D Generation from a Single Image
• HierOctFusion: Multi-scale Octree-based 3D Shape Generation via Part-Whole-Hierarchy Message Passing
• Multi-scale Latent Point Consistency Models for 3D Shape Generation
• Depth-supervised NeRF: Fewer Views and Faster Training for Free
• Sparse-View 3D Reconstruction: Recent Advances and Open Challenges
• The Less You Depend, The More You Learn: Synthesizing Novel Views from Sparse, Unposed Images with Minimal 3D Knowledge
• SyncDreamer: Generating Multiview-consistent Images from a Single-view Image
• Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model
• DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation
• WaveletGaussian: Wavelet-domain Diffusion for Sparse-view 3D Gaussian Object Reconstruction
• AugGS: Self-augmented Gaussians with Structural Masks for Sparse-view 3D Reconstruction

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