Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

A collection of pre-trained, state-of-the-art models in the ONNX format

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

A collection of computer vision pre-trained models.

Highly Accurate and Efficient Burn detection and Classification trained with Deep Learning Model

Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

PyTorch implementation of the CVPR 2019 paper “Pyramid Feature Attention Network for Saliency Detection”

中文文本分类实践，基于搜狗新闻语料库，采用传统机器学习方法以及预训练模型等方法

PyTorch implementation of Darknet53

C++ trainable detection library based on libtorch (or pytorch c++). Yolov4 tiny provided now.

Pretrained SimCLRv2 models in Pytorch

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

Pytorch implementation of Noisy Student Training for Automatic Speech Recognition and Automatic Pronunciation Error Detection problem

Image Synthesis + Corgis = <3

Mask R-CNN, FPN, LinkNet, PSPNet and UNet with multiple backbone architectures support readily available

This is an Image Super Resolution model implemented in python using keras. This model comes with a GUI to allow users to make use of the model easily.

自监督目标检测。针对目标检测任务，提出无需标签数据的自监督算法预训练 backbone，检测性能优于有标签的预训练。

Presenting Collection of Pretrained Models. Links to pretrained models in NLP and voice.

DenseCL + regionCL-D

This GitHub repository contains converted models in ONNX, TensorRT, and PyTorch formats, along with inference scripts and demos. These models can be used for efficient deployment and inference in machine learning applications.