1247 Open source projects that are alternatives of or similar to MNIST-invert-color

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation

A collection of arbitrary text to image papers with code (constantly updating)

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

A Tensorflow implementation of Deep Convolutional Generative Adversarial Networks trained on Fashion-MNIST, CIFAR-10, etc.

Collection of generative models in Tensorflow

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

Image-to-image translation with conditional adversarial nets

Discovering Interpretable GAN Controls [NeurIPS 2020]

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

Applied Deep Learning (2019 Spring) @ NTU

Tensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.

Collection of generative models in Pytorch version.

The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".

Focal Frequency Loss for Generative Models

Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.

Generative Adversarial Network for single image super-resolution in high content screening microscopy images

Image-to-Image Translation in PyTorch

Machine Learning and having it Deep and Structured (MLDS) in 2018 spring

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

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

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

The implementation of Relativistic average GAN with Keras

PyTorch reimplementation of the paper: "Semantic Pyramid for Image Generation" [CVPR 2020].

Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)

🎎 InfoGAN: Interpretable Representation Learning

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

[ECCV 2020 Spotlight] A Simple and Versatile Framework for Image-to-Image Translation

GAN in Tensorflow to be run via Linux command line

Pytorch deep learning face frontalization model

A DCGAN to generate anime faces using custom mined dataset

DCGAN image generator 🖼️.

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

GANnotation (PyTorch): Landmark-guided face to face synthesis using GANs (And a triple consistency loss!)

TF implementation of our ECCV 2018 paper: Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

A stable algorithm for GAN training

OpenMMLab Image and Video Editing Toolbox

Code for GAN2Shape (ICLR2021 oral)

(WIP) Implementation of Creative Adversarial Networks https://arxiv.org/pdf/1706.07068.pdf

Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs (CVPRW 2020)

Train a StyleGAN2 model on Colaboratory to generate Steam banners.

See Triple-GAN-V2 in PyTorch: https://github.com/taufikxu/Triple-GAN

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.

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

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

ArtGAN: This work presents a series of new approaches to improve Generative Adversarial Network (GAN) for conditional image synthesis and we name the proposed model as “ArtGAN”. Implementations are in Caffe/Tensorflow.

Unofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)

Use keras.js and cyclegan-keras to colorize manga automatically. All computation in browser. Demo is online:

Generative Adversarial Network that learns to generate handwritten digits. (Learning Purposes)

FineGAN: Unsupervised Hierarchical Disentanglement for Fine-grained Object Generation and Discovery

Unsupervised anomaly detection with generative model, keras implementation

Tensorflow implementation for Conditional Convolutional Adversarial Networks.

On the "steerability" of generative adversarial networks

GIF is a photorealistic generative face model with explicit 3D geometric and photometric control.

The Implementation of paper "Controllable Person Image Synthesis with Attribute-Decomposed GAN"

Invert a given color.

A sketch extractor for anime/illustration.

Automatic feature engineering using Generative Adversarial Networks using Deeplearning4j and Apache Spark.

A curated list of dedicated resources and applications

Generative Adversarial Networks in TensorFlow 2.0