Lists (9)
Stars
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Reference PyTorch implementation and models for DINOv3
Playing Pokemon Red with Reinforcement Learning
COCO API - Dataset @ http://cocodataset.org/
NVIDIA Isaac GR00T N1.6 - A Foundation Model for Generalist Robots.
🎓 无需编写任何代码即可轻松创建漂亮的学术网站 Easily create a beautiful academic résumé or educational website using Hugo and GitHub. No code.
CoTracker is a model for tracking any point (pixel) on a video.
A small package to create visualizations of PyTorch execution graphs
Bayesian optimization in PyTorch
Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.
[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse m…
Massively parallel rigidbody physics simulation on accelerator hardware.
A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.
An open-source library for GPU-accelerated robot learning and sim-to-real transfer.
Benchmarking Knowledge Transfer in Lifelong Robot Learning
PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks
CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.rea…
A library for developing deep generative models in a more concise, intuitive and extendable way
A working draft of a free undergraduate robotics textbook, collected from lecture notes
optimization routines for hyperparameter tuning
Nvidia GEAR Lab's initiative to solve the robotics data problem using world models