This repository contains the code for the CVPR 2021 paper "GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields"
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Updated
Feb 9, 2022 - Python
This repository contains the code for the CVPR 2021 paper "GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields"
Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more.
PET-NeuS: Positional Encoding Tri-Planes for Neural Surfaces (CVPR 2023)
HF-NeuS: Improved Surface Reconstruction Using High-Frequency Details (NeurIPS 2022)
Reference implementation for "Massively Parallel Rendering of Complex Closed-Form Implicit Surfaces" (SIGGRAPH 2020)
Source code for the Computer Graphics Forum paper: Segment Tracing Using Local Lipschitz Bounds. Presented at Eurographics 2020.
[3DV 2024] Color-NeuS: Reconstructing Neural Implicit Surfaces with Color
blazing fast implicit surface evaluation
GPU-accelerated math function graphers in web browsers, both 3D and 2D.
three.js addon for triangulation of implicit surfaces and for forms with holes. The addon generates indexed BufferGeometries.
🧱 Library for Geometric / Solid Modelling based on 🪐 Implicit Surfaces modelling. (Feel free to submit Pull Requests)
C++ version based on the Marching Cubes library of the paper: http://jcgt.org/published/0008/03/01
Source code for the TOG paper: Terrain Amplification with Implicit 3D Features. Presented at Siggraph Asia 2019.
3D/2D CAD design package written in Go. GPU accelerated.
Reference implementation for "Temporal Set Inversion for Animated Implicits" (SIGGRAPH 2023)
Source code for our Computer Graphics Forum paper: Synthesizing Geologically Coherent Cave Networks
Factored-NeuS: Reconstructing Surfaces, Illumination, and Materials of Possibly Glossy Objects
Data-Driven 3D Reconstruction of Dressed Humans from Sparse Views
Volumetric and implicit surfaces (SDF) pathtracer implementation built on top of Yocto/GL.
Latest version of the Marching Cubes library described in the paper: http://jcgt.org/published/0008/03/01
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