Official implementation of the SIGGRAPH 2024 paper "A Hierarchical 3D Gaussian Representation for Real-Time Rendering of Very Large Datasets"

Python tool for converting files and office documents to Markdown.

This repository contains the official authors implementation associated with the paper "Neural Surface Priors for Editable Gaussian Splatting"

3D Reconstruction for all

[NeurIPS 2024]GSDF: 3DGS Meets SDF for Improved Rendering and Reconstruction

Easy NeRF synthetic dataset creation within Blender

Three.js-based implementation of 3D Gaussian splatting

macOS open source clipboard manager

Geometric Computer Vision Library for Spatial AI

A detailed formulae explanation on gaussian splatting

Flax is a neural network library for JAX that is designed for flexibility.

JavaScript 3D Library.

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Open source platform for the machine learning lifecycle

Open3D: A Modern Library for 3D Data Processing

An extension of Open3D to address 3D Machine Learning tasks

3D Gaussian Splat Editor

Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"

Implementation of the Chamfer Distance as a module for pyTorch

COLMAP - Structure-from-Motion and Multi-View Stereo

Lightweight Physically-Based Renderer designed for ease of use and fast prototyping

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

A collection of 3D reconstruction papers in the deep learning era.

[SIGGRAPH'24] 2D Gaussian Splatting for Geometrically Accurate Radiance Fields

Container runtimes on macOS (and Linux) with minimal setup

Code for our CVPR'23 paper - "PermutoSDF: Fast Multi-View Reconstruction with Implicit Surfaces using Permutohedral Lattices"

Curated list of papers and resources focused on 3D Gaussian Splatting, intended to keep pace with the anticipated surge of research in the coming months.

Materials of the Nordic Probabilistic AI School 2022.

A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

A differentiable PDE solving framework for machine learning