MSA8D8

MSA8D8's Stars

• huggingface/pytorch-image-models

  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

  Language:Python32.8k3189474.8k

• google-research/vision_transformer

  Language:Jupyter Notebook10.7k1062071.3k

• mlfoundations/open_clip

  An open source implementation of CLIP.

  Language:Python10.7k815061k

• facebookresearch/dinov2

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

  Language:Jupyter Notebook9.6k96411852

• facebookresearch/ImageBind

  ImageBind One Embedding Space to Bind Them All

  Language:Python8.5k9993782

• facebookresearch/moco

  PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

  Language:Python4.8k52135796

• facebookresearch/vissl

  VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

  Language:Jupyter Notebook3.3k54173334

• 0x48piraj/fadblock

  Friendly Adblock for YouTube: A fast, lightweight, and undetectable YouTube Ads Blocker for Chrome, Opera and Firefox.

  Language:CSS2.4k15235113

• baaivision/EVA

  EVA Series: Visual Representation Fantasies from BAAI

  Language:Python2.4k30163170

• sthalles/SimCLR

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

  Language:Jupyter Notebook2.3k2158467

• facebookresearch/swav

  PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

  Language:Python2k41116283

• lucidrains/byol-pytorch

  Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch

  Language:Python1.8k2683248

• MadryLab/robustness

  A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.

  Language:Jupyter Notebook9241983181

• OML-Team/open-metric-learning

  Metric learning and retrieval pipelines, models and zoo.

  Language:Python8991122965

• ray-project/tutorial

  Language:Jupyter Notebook7833159212

• Spijkervet/SimCLR

  PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.

  Language:Python769835166

• bytedance/ibot

  iBOT :robot:: Image BERT Pre-Training with Online Tokenizer (ICLR 2022)

  Language:Jupyter Notebook68863578

• LAION-AI/CLIP_benchmark

  CLIP-like model evaluation

  Language:Jupyter Notebook642126581

• jeanfeydy/geomloss

  Geometric loss functions between point clouds, images and volumes

  Language:Python608137362

• facebookresearch/msn

  Masked Siamese Networks for Label-Efficient Learning (https://arxiv.org/abs/2204.07141)

  Language:Python452122433

• dicarlolab/CORnet

  [NeurIPS'19 Oral] CORnet: Modeling the Neural Mechanisms of Core Object Recognition

  Language:Python253171666

• ViCCo-Group/thingsvision

  Python package for extracting representations from state-of-the-art computer vision models

  Language:Python15767621

• braingpt-lovelab/BrainBench

  Source code for <Large language models surpass human experts in predicting neuroscience results>

  61009

• thibsej/unbalanced_gromov_wasserstein

  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport

  Language:Jupyter Notebook434412

• ml-jku/MIM-Refiner

  A Contrastive Learning Boost from Intermediate Pre-Trained Representations

  Language:Python398124

• kakaobrain/coyo-vit

  ViT trained on COYO-Labeled-300M dataset

  Language:Python30721

• ViCCo-Group/SPoSE

  Sparse Positive Object Similarity Embedding(s)

  Language:Python11567

• florianmahner/object-dimensions

  Code accompanying the paper "Dimensions underlying the representational alignment of deep neural networks with humans"

  Language:Python4310

• CPJKU/performance_embeddings_fire23

  Language:Jupyter Notebook320

• psiz-org/psiz-datasets

  Collection of curated datasets for use with PsiZ.

  Language:Python110