Neural Depth Field advances 3D geometry inpainting and reconstruction

Researchers have introduced the Neural Depth Field (NDF), a novel approach to reconstructing and inpainting incomplete 3D scene geometry. Unlike traditional depth estimators, NDF treats depth estimation as a scene-level implicit field, allowing it to adapt to specific domains while maintaining consistency with observed geometry. This method has demonstrated significant improvements, reducing cross-view inconsistency by 63.3% and enhancing inpainting accuracy by 23.1%, setting a new state-of-the-art performance for 3D scene geometry inpainting across various data types, including indoor scans and satellite imagery. AI

IMPACT Advances 3D scene reconstruction and inpainting capabilities, potentially improving applications in robotics, AR/VR, and autonomous systems.

RANK_REASON The cluster contains a research paper published on arXiv detailing a new method for 3D scene geometry inpainting and reconstruction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• alphaXiv
• arXiv
• CatalyzeX Code Finder for Papers
• computer science
• Computer vision and pattern recognition
• Connected Papers
• CORE Recommender
• DagsHub
• Gotit.pub
• Hugging Face
• Influence Flower
• Litmaps
• Neural Depth Field
• ScienceCast
• scite Smart Citations

• paper
• other

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →