There are 3 repositories under pretrained-weights topic.
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
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Classification models trained on ImageNet. Keras.
Pretrained TorchVision models on CIFAR10 dataset (with weights)
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
YOLOv3 implementation in TensorFlow 2.3.1
Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)
A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.
PyTorch Lightning Optical Flow models, scripts, and pretrained weights.
Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL)
An Out-of-the-Box Replication of GANimation using PyTorch, pretrained weights are available!
A Beautiful Flask Web API for Yolov7 (and custom) models
https://towardsdatascience.com/tutorial-build-an-object-detection-system-using-yolo-9a930513643a
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)
A native Tensorflow implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions (2016). Optionally uses the pretrained weights by the authors.
Pretrained is the most complete and frequently updated list of pretrained top-performing models. Tensorflow, Theano and others. Want to add your model? File an issue, and we will add it.
Multi-label classification based on timm.
C++ trainable detection library based on libtorch (or pytorch c++). Yolov4 tiny provided now.
The MAMA-MIA Dataset: A Multi-Center Breast Cancer DCE-MRI Public Dataset with Expert Segmentations
Address book for computer vision models.
It is a comprehensive resource hub compiling all LLM papers accepted at the International Conference on Learning Representations (ICLR) in 2024.
Pytorch EfficientNetV2 EfficientNetV1 with pretrained weights
An implementation of MobileNetV3 with pyTorch
Fight Detection From Surveillance Cameras by fine-tuning a PyTorch Pretrained Model
A Pytorch implementation of the 2017 Huang et. al. paper "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization"
Multi-label classification based on timm, and add SimCLR to timm.
Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights.
Pytorch implements yolov3.Good performance, easy to use, fast speed.
Pre-trained NFNets with 99% of the accuracy of the official paper "High-Performance Large-Scale Image Recognition Without Normalization".
This project shows Image Super Resolution using Deep Learning . Seven models are implemented SRCNN, FSRCNN,ESPCN, RDN, RFDN, Autoencoder and ESRGAN.
TensorFlow version of SqueezeNet with converted pretrained weights
RAIL: Region-Aware Instructive Learning for Semi-Supervised Tooth Segmentation in CBCT