[NeurIPS 2025] LiteReality: Graphics-Ready 3D Scene Reconstruction from RGB-D Scans

Your API ⇒ Paid MCP. Instantly.

A General NeRF Acceleration Toolbox in PyTorch.

Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion.

An awesome PyTorch NeRF library

Implementation of Video Diffusion Models, Jonathan Ho's new paper extending DDPMs to Video Generation - in Pytorch

Official PyTorch Implementation of "GAN-Supervised Dense Visual Alignment" (CVPR 2022 Oral, Best Paper Finalist)

Implementation of ConvMixer for "Patches Are All You Need? 🤷"

Pytorch Lightning Distributed Accelerators using Ray

EPOS: Estimating 6D Pose of Objects with Symmetries, CVPR 2020

Marching cubes with and without color interpolation, and edge subsampling.

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

Official implementation of "Articulation Aware Canonical Surface Mapping"

Code release for "Canonical Surface Mapping via Geometric Cycle Consistency"

Simulating Kinect Noise: adding noise to clean depth-maps rendered with a graphics engine.

A toolkit for robot learning research.

3D Point Capsule Networks

Transporter implementation in PyTorch

Python library for loading and using triangular meshes.

Neural-Guided, Differentiable RANSAC for Camera Re-Localization (NG-DSAC++)

Unsupervised learning of Object Landmarks through Conditional Image Generation

Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"

[CVPR'19] JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds

💦 Seamless, distributed, real-time integration of Blender into PyTorch data pipelines

Code for reproducing key results in the paper "InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets"

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning