1222 Open source projects that are alternatives of or similar to Tensorflow Srgan

A modern PyTorch implementation of SRGAN

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

ICCV 2019 (oral) RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution. PyTorch implementation

Official repository of JSI-GAN (Accepted at AAAI 2020).

Official PyTorch implementation of "Artist Style Transfer Via Quadratic Potential"

Using Machine Learning to predict the type of exercise from movement data

Awesome GAN for Medical Imaging

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution

Deep Learning Super Sampling with Deep Convolutional Generative Adversarial Networks.

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

Pytorch implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

[TIP2020] Pytorch implementation of "Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network"

A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

The Simplest DCGAN Implementation

Code for deep generative prior (ECCV2020 oral)

PyTorch code for "PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer" (CVPR 2020 Oral)

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

🦓<->🦒 🌃<->🌆 A collection of image to image papers with code (constantly updating)

A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps

This repository contains a new generative model of chatbot based on seq2seq modeling.

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

由淺入深的深度學習資源 Collection of deep learning materials for everyone

A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation

A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).

[CVPR2020] Adversarial Latent Autoencoders

An extremely simple generative adversarial network, built with TensorFlow

A simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)

Official repository for the paper "High-Resolution Daytime Translation Without Domain Labels" (CVPR2020, Oral)

Create Anime Characters with MakeGirlsMoe

The official implementation of our SIGGRAPH 2020 paper Interactive Video Stylization Using Few-Shot Patch-Based Training

Keras implementation of 3D Generative Adversarial Network.

Synthetic Data Generation for tabular, relational and time series data.

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

Interactive Image Generation via Generative Adversarial Networks

GAN Playground - Experiment with Generative Adversarial Nets in your browser. An introduction to GANs.

Implementation of Apple's Learning from Simulated and Unsupervised Images through Adversarial Training

Solve captcha without manually labeling a training set

Tensorflow implementation of Wasserstein GAN - arxiv: https://arxiv.org/abs/1701.07875

Pytorch implementation of "DeepFlow: History Matching in the Space of Deep Generative Models"

T2F: text to face generation using Deep Learning

TextGAN is a PyTorch framework for Generative Adversarial Networks (GANs) based text generation models.

Introduction to generative adversarial networks, with code to accompany the O'Reilly tutorial on GANs

👔👗🕶️🎩 Cool resources about Fashion + AI! (papers, datasets, workshops, companies, ...) (constantly updating)

Generate your own cartoon-style images with CartoonGAN (CVPR 2018), powered by TensorFlow 2.0 Alpha.

Synthesizing and manipulating 2048x1024 images with conditional GANs

Dataset and Code for our CVPR'18 paper ST-CGAN: "Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal"

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

Awesome Generative Adversarial Networks with tensorflow

Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

Generative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

An application tool of edge-connect, which can do anime inpainting and drawing. 动漫人物图片自动修复，去马赛克，填补，去瑕疵

A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.