There are 3 repositories under pretrained-weights topic.
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
Segmentation models with pretrained backbones. PyTorch.
Classification models trained on ImageNet. Keras.
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
YOLOv3 implementation in TensorFlow 2.3.1
Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL)
Pretrained TorchVision models on CIFAR10 dataset (with weights)
Easily train or fine-tune SOTA computer vision models with one open source training library
EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation
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.
An Out-of-the-Box Replication of GANimation using PyTorch, pretrained weights are available!
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.
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)
End-to-End Vietnamese Speech Recognition using wav2vec 2.0
C++ trainable detection library based on libtorch (or pytorch c++). Yolov4 tiny provided now.
I3D implemetation in Keras + video preprocessing + visualization of results
An implementation of MobileNetV3 with pyTorch
TensorFlow version of SqueezeNet with converted pretrained weights
Pre-trained NFNets with 99% of the accuracy of the official paper "High-Performance Large-Scale Image Recognition Without Normalization".
Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights.
Address book for computer vision models.
A Pytorch implementation of the 2017 Huang et. al. paper "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization"
Pytorch implements yolov3.Good performance, easy to use, fast speed.
Multi-label classification based on timm, and add SimCLR to timm.
pytorch implementation of several CNNs for image classification
Experiment with pre-training spaCy
Pretrained Efficient DenseNet Model
A deep learning model built to detect cataract in human eyes using the VGG-19 pretrained weights
Uisng Deep Sort + Yolov3 model Pretrained on COCO dataset for passenger detection and counting
Fight Detection From Surveillance Cameras by fine-tuning a PyTorch Pretrained Model
Pytorch EfficientNetV2 EfficientNetV1 with pretrained weights
In this assignment I have to build a Mask R-CNN based keypoint detector model using Detectron2. Detectron2 was written in PyTorch and contains many state-of-the-art obejct detection models with pretrained weights.