Lorna

SRGAN-PyTorch. A simple and complete implementation of super-resolution paper.

CycleGAN-PyTorch. A very simple implementation of cyclegan, which is based on pytorch.

ESRGAN-PyTorch. A simple implementation of esrgan, which uses the pytorch framework.

SRCNN-PyTorch. Pytorch framework can easily implement srcnn algorithm with excellent performance

ESPCN-PyTorch. A PyTorch implementation of ESPCN based on CVPR 2016 paper Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network.

FSRCNN-PyTorch. Fast implementation of fsrcnn algorithm based on pytorch framework

AlexNet-PyTorch. An PyTorch implementation AlexNet.Simple, easy to use and efficient

machine_learning_in_action_py3. Important book about the machine learning algorithms, and introduces the application of those who use these algorithms and tools, and how to use them in a real environment. This book and other books, behind the other books are long on machine learning theory knowledge, the book happened to be more discussion on how to use coded machine learning algorithms.

VDSR-PyTorch. PyTorch implements "Accurate Image Super-Resolution Using Very Deep Convolutional Networks"

RFB_ESRGAN-PyTorch. Simple realization of papers in oppo Research Institute super score competition.

conditional_gan. Simple implementation of conditional general adverse nets in pytorch machine learning framework

GoogLeNet-PyTorch. Restore the official code 100% and improve it to make it easier to use.

WassersteinGAN_GP-PyTorch. Improved training of Wasserstein GANs

ResNet-PyTorch. PyTorch implements `Deep Residual Learning for Image Recognition` paper.

VGG-PyTorch. The implementation of VGG thesis is implemented under PyTorch framework

Real_ESRGAN-PyTorch. PyTorch implements `Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data` paper.

YOLOv3-PyTorch. Pytorch implements yolov3.Good performance, easy to use, fast speed.

YOLOv4-PyTorch. Pytorch implements yolov4.Good performance, easy to use, fast speed.

UGATIT-PyTorch. Simple, fast and easy to read. Yes, we use the pytorch framework!

GAN-PyTorch. A complete implementation of the Pytorch neural network framework for GAN

pytorch-tutorial. fork Yunjey Choi/ [@yunjey](https://github.com/yunjey)

PyTorch-WGANGP. PyTorch implements WGAN_GP

pytorch-alexnet-cifar100. Cifar100 in alexnet network model under the highest accuracy

WassersteinGAN_DIV-PyTorch. Wasserstein Divergence for GANs

DCGAN-PyTorch. PyTorch implements a Deep Convolution GAN neural network structure

PyTorch-NCSN. This is the best GAN method to generate cifar-10

PyTorch. An open source deep learning platform that provides a seamless path from research prototyping to production deployment

MobileNetV1-PyTorch. PyTorch implements `MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications` paper.

RCAN-PyTorch. PyTorch implements `Image Super-Resolution Using Very Deep Residual Channel Attention Networks` paper.

SwinIR-PyTorch. PyTorch implements `SwinIR: Image Restoration Using Swin Transformer` paper.

InceptionV4-PyTorch. PyTorch implements `Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning` paper.

MetaSR-PyTorch. PyTorch implements `Meta-SR: A Magnification-Arbitrary Network for Super-Resolution` paper

pytorch-inception-v3-cifar100. Pytorch implements the inceptionv4 model for cifar100 classification

TensorFlow2-tutorials. This is a tutorial from TensorFlow's website, thanks to Google Inc

pytorch-vgg19-cifar100. Pytorch implements the VGG19 model to classify cifar100

CRNN-PyTorch. PyTorch implemnts `An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition` paper.

DenseNet-PyTorch. Restore the official code 100% and improve it to make it easier to research and facilitate production.

SRDenseNet-PyTorch. PyTorch implements `Image Super-Resolution Using Dense Skip Connections` paper.

Deep-learning-paper-CN. Deep learning thesis Chinese translation, including object classification, detection.

PyTorch-pix2pixHD. PyTorch implements high resolution image generation

InceptionV3-PyTorch. PyTorch implements `Rethinking the Inception Architecture for Computer Vision` paper.

TensorFlow-MNIST. MNIST, KMNIST, EMNIST and others have TensorFlow implementation of handwritten data set, based on TF2 version

tf-gans. Tensorflow implements the most primitive GAN

CSNLN-PyTorch. PyTorch implemnts `Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining` paper.

PyTorch-CIFAR. The classification of the CIFAR dataset is carried out by using the PyTorch learning framework and the most advanced method model.（使用PyTorch学习框架来对CIFAR数据集的分类，采用最先进的方法模型来实现。）

PyTorch-MNIST. PyTorch is an item library for MNIST dataset competition

PyTorch-StyleGAN. PyTorch implements StyleGAN

zero2BGD. Numpy implements BGD

Video_2_Char. CAI xukun is so handsome in basketball!

PyTorch-InfoGAN. PyTorch implementation InfoGAN

My-girlfriend. I miss you

face_recognition. Open source framework on fork, easy to implement

target_detection. Target detection based on the Pytorch framework.

PaDiM. PyTorch unofficial implements `PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization` paper.

QtStartQuicklyTutorial. Quick start tutorial under QT Framework based on C++

SAGAN-PyTorch. PyTorch unoffical implemnts `Self-Attention Generative Adversarial Networks` paper.

StarGANv2-PyTorch. PyTorch implements `StarGAN v2: Diverse Image Synthesis for Multiple Domains` paper.

RepVGG-PyTorch. PyTorch implements `RepVGG: Making VGG-style ConvNets Great Again` paper.

ContextualLoss-PyTorch. PyTorch implements `Maintaining Natural Image Statistics with the Contextual Loss` paper.

PDM-PyTorch. PyTorch implements `Learning the Degradation Distribution for Blind Image Super-Resolution` paper.