mhamilton723/FeatUp

Let us democratise high-resolution generation! (CVPR 2024)

Efficient vision foundation models for high-resolution generation and perception.

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

Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.

Reference PyTorch implementation and models for DINOv3

Official repository for "AM-RADIO: Reduce All Domains Into One"

Scenic: A Jax Library for Computer Vision Research and Beyond

Collection of common code that's shared among different research projects in FAIR computer vision team.

The repository provides code for running inference and finetuning with the Meta Segment Anything Model 3 (SAM 3), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.