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.

Google Research

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.

Code release for NeRF (Neural Radiance Fields)

PyTorch code and models for the DINOv2 self-supervised learning method.

Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

Efficient neural feature detector and descriptor

Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629

D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

TartanAir dataset tools and samples

[CVPR 2023 Highlight] Perspective Fields for Single Image Camera Calibration

Long-Term Object Visual SLAM

Combating hidden stratification with GEORGE

Neural Network Bayesian Kernel Inference.

Triplet Dataset Toolkit for the 3RScan Dataset