Apr 20, 2021 · Our key insight is that implicit surface models and radiance fields can be formulated in a unified way, enabling both surface and volume rendering using the same model. This unified perspective enables novel, more efficient sampling procedures and the ability to reconstruct accurate surfaces without input masks.

Our key insight is that implicit surface models and radiance fields can be formulated in a unified way, enabling both surface and volume rendering using the same model. This unified perspective enables novel, more efficient sampling procedures and the ability to reconstruct accurate surfaces without input masks.

We compare our method on the DTU, BlendedMVS, and a syn- thetic indoor dataset. Our experiments demonstrate that we outperform NeRF in terms of reconstruction quality while performing on par with IDR without requiring masks. TL;DR: Unification of Occupancy Networks and Neural Radiance Fields for 3D reconstruction. Bibtex:

UNISURF was a pioneering surface CAD/CAM system, designed to assist with car body design and tooling. It was developed by French engineer Pierre Bézier for Renault in 1968, and entered full use at the company in 1975.

Contributions: In this paper, we propose UNISURF (UNI-fied Neural Implicit SUrface and Radiance Fields) a prin-cipled unified framework for implicit surfaces and radi-ance fields, with the goal of reconstructing solid (i.e., non-transparent) objects from a set of RGB images.

UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction Abstract: Neural implicit 3D representations have emerged as a powerful paradigm for reconstructing surfaces from multi-view images and synthesizing novel views.

UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction Michael Oechsle, Songyou Peng, and Andreas Geiger ICCV 2021 (Oral) Neural implicit 3D representations have emerged as a powerful paradigm for reconstructing surfaces from multi-view images and synthesizing novel views.

Jun 16, 2023 · SDFStudio is a unified and modular framework for neural implicit surface reconstruction, built on top of the awesome nerfstudio project. We provide a unified implementation of three major implicit surface reconstruction methods: UniSurf, VolSDF, and …

UNISURF provides a principled unified formulation, enabling accurate surface reconstruction from images without input masks. Capturing the geometry and appearance of 3D scenes from a set of images is one of the cornerstone problems in computer vision.

SDFStudio is a unified and modular framework for neural implicit surface reconstruction, built on top of the awesome nerfstudio project. We provide a unified implementation of three major implicit surface reconstruction methods: UniSurf, VolSDF, and NeuS.