Instant neural graphics primitives: lightning fast NeRF and more
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Updated
Feb 13, 2023 - Cuda
Instant neural graphics primitives: lightning fast NeRF and more
Simple SDF mesh generation in Python
Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives: https://nvlabs.github.io/instant-ngp/
A simple CAD package using signed distance functions
a playground for making 3D art with lisp and math
Create, ray trace & export programatically defined Signed Distance Function CSG geometries with an API suited for generative art - in your browser!
Euclidean distance & signed distance transform for multi-label 3D anisotropic images using marching parabolas.
Marching cubes with and without color interpolation, and edge subsampling.
Fast and light-weight Marching Cubes library in C++ without any dependencies.
Pytorch code for ECCV'22 paper. ShAPO: Implicit Representations for Multi-Object Shape, Appearance and Pose Optimization
Signed is a 3D modeling and construction language based on Lua and SDFs. Signed will be available for macOS and iOS and is heavily optimized for Metal.
Signed Distance Function from triangle mesh.
A Flexible Framework for Robot Control in Python
Sphere tracing signed distance functions.
A Go library for signed distance function shape generation.
Implementation of Differentiable Sign-Distance Function Rendering - in Pytorch
Make complex Ray Marching SDF objects using nodes with the Material Maker editor and this library
Source code for the paper: Modeling Rocky Scenery using Implicit Blocks, published in The Visual Computer and presented at Computer Graphics International 2020.
A fast and cross-platform Signed Distance Function (SDF) viewer, easily integrated with your SDF library.
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