scikit-learn: machine learning in Python

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.

Open standard for machine learning interoperability

An open source implementation of CLIP.

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

DUSt3R: Geometric 3D Vision Made Easy

Single Image to 3D using Cross-Domain Diffusion for 3D Generation

A PyTorch Library for Accelerating 3D Deep Learning Research

A pytorch CUDA extension implementation of instant-ngp (sdf and nerf), with a GUI.

SMPL-X

Hopfield Networks is All You Need

Code release for NeuS

NVIDIA Kaolin Wisp is a PyTorch library powered by NVIDIA Kaolin Core to work with neural fields (including NeRFs, NGLOD, instant-ngp and VQAD).

A General NeRF Acceleration Toolbox in PyTorch.

Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition (CVPR2023)

Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

arxiv-sanity lite: tag arxiv papers of interest get recommendations of similar papers in a nice UI using SVMs over tfidf feature vectors based on paper abstracts.

Direct voxel grid optimization for fast radiance field reconstruction.

ONNXMLTools enables conversion of models to ONNX

HOTA (and other) evaluation metrics for Multi-Object Tracking (MOT).

1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.

Neural Surface reconstruction based on Instant-NGP. Efficient and customizable boilerplate for your research projects. Train NeuS in 10min!

Implementations of NeRF variants based on Taichi + PyTorch

an implementation of softmax splatting for differentiable forward warping using PyTorch

InstantAvatar: Learning Avatars from Monocular Video in 60 Seconds (CVPR 2023)