Matisse: Evidence-Space Reasoning for Active 3D Reconstruction

arXiv:2609.38746 · cs.CV, cs.RO · Submitted 2026-09-30 · Read on arXiv

cs.CV, cs.RO

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Information Gain — 32× in this paper · explained in 2 episodes
• Gaussian Splatting — 10× in this paper · explained in 4 episodes
• Evidential Uncertainty — 9× in this paper
• Generative Model — 9× in this paper · explained in 2 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Computer Vision and Pattern Recognition — 6× in this paper
• Adaptive Evidential Memory — 5× in this paper
• Evidential Information Gain — 5× in this paper
• Active Perception — 4× in this paper · explained in 2 episodes
• Diffusion Model — 4× in this paper · explained in 8 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• 3D Gaussian Splatting — 3× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Diffusion Models — 3× in this paper · explained in 6 episodes
• Training-Free Framework — 3× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• International Conference on Robotics and Automation — 2× in this paper
• Latent Representation — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Active SLAM — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Epistemic Uncertainty — 1× in this paper · explained in 10 episodes
• Fisher Information — 1× in this paper · explained in 3 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Quantifying Uncertainty — 1× in this paper · explained in 5 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Items
• Conffusion: Confidence Intervals for Diffusion Models
• Generative Uncertainty in Diffusion Models
• Informative Object-centric Next Best View for Object-aware 3D Gaussian Splatting in Cluttered Scenes
• SA-ResGS: Self-Augmented Residual 3D Gaussian Splatting for Next Best View Selection
• MV-SAM3D: Adaptive Multi-View Fusion for Layout-Aware 3D Generation
• VGGT-SLAM 2.0: Real-time Dense Feed-forward Scene Reconstruction
• GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction
• The Replica Dataset: A Digital Replica of Indoor Spaces
• DVD: Discrete Voxel Diffusion for 3D Generation and Editing
• World Tracing: Generative Pixel-Aligned Geometry Beyond the Visible
• Stream3D: Sequential Multi-View 3D Generation via Evidential Memory

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models