lightly-ai/lightly

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

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

Scenic: A Jax Library for Computer Vision Research and Beyond

Datasets, Transforms and Models specific to Computer Vision

OpenMMLab Pre-training Toolbox and Benchmark

PyTorch code and models for V-JEPA self-supervised learning from video.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

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

Reference PyTorch implementation and models for DINOv3