Alternatives and similar repositories for PhotographicImageSynthesis

Users that are interested in PhotographicImageSynthesis are comparing it to the libraries listed below

• yunjey / domain-transfer-network
  TensorFlow Implementation of Unsupervised Cross-Domain Image Generation
  ☆862Updated 7 years ago
• yenchenlin / pix2pix-tensorflow
  TensorFlow implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".
  ☆938Updated 6 years ago
• LouieYang / deep-photo-styletransfer-tf
  Tensorflow (Python API) implementation of Deep Photo Style Transfer
  ☆810Updated 3 years ago
• bamos / dcgan-completion.tensorflow
  Image Completion with Deep Learning in TensorFlow
  ☆1,320Updated 8 years ago
• carpedm20 / BEGAN-tensorflow
  Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
  ☆926Updated 7 years ago
• msracver / Deep-Image-Analogy
  The source code of 'Visual Attribute Transfer through Deep Image Analogy'.
  ☆1,371Updated 4 years ago
• leehomyc / Faster-High-Res-Neural-Inpainting
  High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis
  ☆1,296Updated 7 years ago
• carpedm20 / simulated-unsupervised-tensorflow
  TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"
  ☆577Updated 6 years ago
• TuSimple / mx-maskrcnn
  An MXNet implementation of Mask R-CNN
  ☆1,757Updated 7 years ago
• Evolving-AI-Lab / ppgn
  Code for paper "Plug and Play Generative Networks"
  ☆542Updated 7 years ago
• cvondrick / videogan
  Generating Videos with Scene Dynamics. NIPS 2016.
  ☆713Updated 7 years ago
• DmitryUlyanov / texture_nets
  Code for "Texture Networks: Feed-forward Synthesis of Textures and Stylized Images" paper.
  ☆1,226Updated 8 years ago
• ry / tensorflow-vgg16
  conversation of caffe vgg16 model to tensorflow
  ☆674Updated 7 years ago
• rtqichen / style-swap
  code for "Fast Patch-based Style Transfer of Arbitrary Style".
  ☆411Updated 7 years ago
• msracver / FCIS
  Fully Convolutional Instance-aware Semantic Segmentation
  ☆1,564Updated 4 years ago
• SKTBrain / DiscoGAN
  Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
  ☆780Updated 4 years ago
• taki0112 / StarGAN-Tensorflow
  Simple Tensorflow implementation of StarGAN (CVPR 2018 Oral)
  ☆714Updated 6 years ago
• OlavHN / fast-neural-style
  Fast neural style in tensorflow based on http://arxiv.org/abs/1603.08155
  ☆196Updated 9 years ago
• infocusp / tf_cnnvis
  CNN visualization tool in TensorFlow
  ☆779Updated 6 years ago
• hzy46 / fast-neural-style-tensorflow
  A tensorflow implementation for fast neural style!
  ☆930Updated 7 years ago
• torrvision / crfasrnn
  This repository contains the source code for the semantic image segmentation method described in the ICCV 2015 paper: Conditional Random …
  ☆1,342Updated 6 years ago
• hardikbansal / CycleGAN
  Tensorflow implementation of CycleGAN
  ☆381Updated 6 years ago
• facebookresearch / FaderNetworks
  Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017
  ☆765Updated 4 years ago
• carpedm20 / DiscoGAN-pytorch
  PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
  ☆1,100Updated 7 years ago
• tjwei / GANotebooks
  wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch
  ☆1,494Updated 7 years ago
• merantix / picasso
  A CNN visualizer
  ☆1,001Updated 7 years ago
• bourdakos1 / capsule-networks
  A Tensorflow implementation of Capsule Networks
  ☆479Updated 7 years ago
• buriburisuri / SRGAN
  A tensorflow implemenation of Christian et al's SRGAN(super-resolution generative adversarial network)
  ☆287Updated 8 years ago
• sunshineatnoon / Paper-Implementations
  Use PyTorch to implement some classic frameworks
  ☆623Updated 8 years ago
• dyelax / Adversarial_Video_Generation
  A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.
  ☆745Updated 4 years ago