Curated list of awesome GAN applications and demo

Overview

banner

gans-awesome-applications

Curated list of awesome GAN applications and demonstrations.

Note: General GAN papers targeting simple image generation such as DCGAN, BEGAN etc. are not included in the list. I mainly care about applications.

The landmark papers that I respect.

  • Generative Adversarial Networks, [paper], [github]
  • Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, [paper], [github]
  • Improved Techniques for Training GANs, [paper], [github]
  • BEGAN: Boundary Equilibrium Generative Adversarial Networks, [paper], [github]

Contents

Use this contents list or simply press command + F to search for a keyword


Applications using GANs

Font generation

  • Learning Chinese Character style with conditional GAN, [blog], [github]
  • Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning, [paper], [github]
  • Attribute2Font: Creating Fonts You Want From Attributes, [paper], [github]

Anime character generation

  • Towards the Automatic Anime Characters Creation with Generative Adversarial Networks, [paper]
  • [Project] A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing, [github]
  • [Project] A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations, [github]
  • [Project] Keras-GAN-Animeface-Character, [github]
  • [Project] A DCGAN to generate anime faces using custom mined dataset, [github]

Interactive Image generation

  • Generative Visual Manipulation on the Natural Image Manifold, [paper], [github]
  • Neural Photo Editing with Introspective Adversarial Networks, [paper], [github]

Text2Image (text to image)

  • TAC-GAN – Text Conditioned Auxiliary Classifier Generative Adversarial Network, [paper], [github]
  • StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks, [paper], [github]
  • Generative Adversarial Text to Image Synthesis, [paper], [github], [github]
  • Learning What and Where to Draw, [paper], [github]

3D Object generation

  • Parametric 3D Exploration with Stacked Adversarial Networks, [github], [youtube]
  • Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling, [paper], [github], [youtube]
  • 3D Shape Induction from 2D Views of Multiple Objects, [paper]
  • Fully Convolutional Refined Auto-Encoding Generative Adversarial Networks for 3D Multi Object Scenes, [github], [blog]

Image Editing

  • Invertible Conditional GANs for image editing, [paper], [github]
  • Image De-raining Using a Conditional Generative Adversarial Network, [paper], [github]

Face Aging

  • Age Progression/Regression by Conditional Adversarial Autoencoder, [paper], [github]
  • CAN: Creative Adversarial Networks Generating “Art” by Learning About Styles and Deviating from Style Norms, [paper]
  • FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS, [paper]

Human Pose Estimation

  • Joint Discriminative and Generative Learning for Person Re-identification, [paper], [github], [video]
  • Pose Guided Person Image Generation, [paper]

Domain-transfer (e.g. style-transfer, pix2pix, sketch2image)

  • Image-to-Image Translation with Conditional Adversarial Networks, [paper], [github], [youtube]
  • Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks, [paper], [github], [youtube]
  • Learning to Discover Cross-Domain Relations with Generative Adversarial Networks, [paper], [github]
  • Unsupervised Creation of Parameterized Avatars, [paper]
  • UNSUPERVISED CROSS-DOMAIN IMAGE GENERATION, [paper]
  • Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks, [paper], [github]
  • Pixel-Level Domain Transfer [paper], [github]
  • TextureGAN: Controlling Deep Image Synthesis with Texture Patches, [paper], [demo]
  • Vincent AI Sketch Demo Draws In Throngs at GTC Europe, [blog], [youtube]
  • Deep Photo Style Transfer, [paper], [github]

Image Inpainting (hole filling)

  • Context Encoders: Feature Learning by Inpainting, [paper], [github]
  • Semantic Image Inpainting with Perceptual and Contextual Losses, [paper], [github]
  • SEMI-SUPERVISED LEARNING WITH CONTEXT-CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS, [paper]
  • Generative Face Completion, [paper], [github]

Super-resolution

  • Image super-resolution through deep learning, [github]
  • Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network, [paper], [github]
  • High-Quality Face Image Super-Resolution Using Conditional Generative Adversarial Networks, [paper]
  • Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network, [paper], [github]

Image Blending

  • GP-GAN: Towards Realistic High-Resolution Image Blending, [paper], [github]

High-resolution image generation (large-scale image)

  • Generating Large Images from Latent Vectors, [blog], [github]
  • PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION, [paper], [github]

Adversarial Examples (Defense vs Attack)

  • SafetyNet: Detecting and Rejecting Adversarial Examples Robustly, [paper]
  • ADVERSARIAL EXAMPLES FOR GENERATIVE MODELS, [paper]
  • Adversarial Examples Generation and Defense Based on Generative Adversarial Network, [paper]

Visual Saliency Prediction (attention prediction)

  • SalGAN: Visual Saliency Prediction with Generative Adversarial Networks, [paper], [github]

Object Detection/Recognition

  • Perceptual Generative Adversarial Networks for Small Object Detection, [paper]
  • Adversarial Generation of Training Examples for Vehicle License Plate Recognition, [paper]

Robotics

  • Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks, [paper], [github]

Video (generation/prediction)

  • DEEP MULTI-SCALE VIDEO PREDICTION BEYOND MEAN SQUARE ERROR, [paper], [github]

Synthetic Data Generation

  • Learning from Simulated and Unsupervised Images through Adversarial Training, [paper], [github]

Others

  • (Physics) Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis, [paper], [github]
  • (Games) STYLE TRANSFER GENERATIVE ADVERSARIAL NETWORKS: LEARNING TO PLAY CHESS DIFFERENTLY, [paper], [github]
  • (General) Spectral Normalization for Generative Adversarial Networks, [paper], [github]

Did not use GAN, but still interesting applications.

Real-time face reconstruction

  • Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction, [paper], [github], [youtube]

Super-resolution

Photorealistic Image generation (e.g. pix2pix, sketch2image)

Human Pose Estimation

  • Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation, [paper], [github]

3D Object generation

  • 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction, [paper], [github]

GAN tutorials with easy and simple example code for starters


Implementations of various types of GANs collection


Trendy AI-application Articles

Author

Minchul Shin, @nashory

Any recommendations to add to the list are welcome :)
Feel free to make pull requests!

Owner
Minchul Shin
Deep Learning, Computer Vision | Research Scientist at kakaobrain (2021-present) | ex-SWE at NAVER (2017-2021)
Minchul Shin
Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance

Models for natural language understanding (NLU) tasks often rely on the idiosyncratic biases of the dataset, which make them brittle against test cases outside the training distribution.

Ubiquitous Knowledge Processing Lab 22 Jan 02, 2023
Code and Data for the paper: Molecular Contrastive Learning with Chemical Element Knowledge Graph [AAAI 2022]

Knowledge-enhanced Contrastive Learning (KCL) Molecular Contrastive Learning with Chemical Element Knowledge Graph [ AAAI 2022 ]. We construct a Chemi

Fangyin 58 Dec 26, 2022
PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices.

PyTorch-LIT PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices. With

Amin Rezaei 157 Dec 11, 2022
This initial strategy was developed specifically for larger pools and is based on taking a moving average and deriving Bollinger Bands to create a projected active liquidity range.

Gamma's Strategy One This initial strategy was developed specifically for larger pools and is based on taking a moving average and deriving Bollinger

Gamma Strategies 46 Dec 02, 2022
The 2nd place solution of 2021 google landmark retrieval on kaggle.

Leaderboard, taxonomy, and curated list of few-shot object detection papers.

229 Dec 13, 2022
“英特尔创新大师杯”深度学习挑战赛 赛道3:CCKS2021中文NLP地址相关性任务

基于 bert4keras 的一个baseline 不作任何 数据trick 单模 线上 最高可到 0.7891 # 基础 版 train.py 0.7769 # transformer 各层 cls concat 明神的trick https://xv44586.git

孙永松 7 Dec 28, 2021
Python and Julia in harmony.

PythonCall & JuliaCall Bringing Python® and Julia together in seamless harmony: Call Python code from Julia and Julia code from Python via a symmetric

Christopher Rowley 414 Jan 07, 2023
PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric (ICCV 2021)

PrimitiveNet Source code for the paper: Jingwei Huang, Yanfeng Zhang, Mingwei Sun. [PrimitiveNet: Primitive Instance Segmentation with Local Primitive

Jingwei Huang 47 Dec 06, 2022
Brain tumor detection using CNN (InceptionResNetV2 Model)

Brain-Tumor-Detection Building a detection model using a convolutional neural network in Tensorflow & Keras. Used brain MRI images. InceptionResNetV2

1 Feb 13, 2022
Surrogate- and Invariance-Boosted Contrastive Learning (SIB-CL)

Surrogate- and Invariance-Boosted Contrastive Learning (SIB-CL) This repository contains all source code used to generate the results in the article "

Charlotte Loh 3 Jul 23, 2022
Active Offline Policy Selection With Python

Active Offline Policy Selection This is supporting example code for NeurIPS 2021 paper Active Offline Policy Selection by Ksenia Konyushkova*, Yutian

DeepMind 27 Oct 15, 2022
Compares various time-series feature sets on computational performance, within-set structure, and between-set relationships.

feature-set-comp Compares various time-series feature sets on computational performance, within-set structure, and between-set relationships. Reposito

Trent Henderson 7 May 25, 2022
😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc

------ Update September 2018 ------ It's been a year since TorchMoji and DeepMoji were released. We're trying to understand how it's being used such t

Hugging Face 865 Dec 24, 2022
Code for Learning to Segment The Tail (LST)

Learning to Segment the Tail [arXiv] In this repository, we release code for Learning to Segment The Tail (LST). The code is directly modified from th

47 Nov 07, 2022
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification

FPGA & FreeNet Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification by Zhuo Zheng, Yanfei Zhong, Ailong M

Zhuo Zheng 92 Jan 03, 2023
Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution Prediction" (NeurIPS-21)

Learning Causal Semantic Representation for Out-of-Distribution Prediction This repository is the official implementation of "Learning Causal Semantic

Chang Liu 54 Dec 01, 2022
Multi-angle c(q)uestion answering

Macaw Introduction Macaw (Multi-angle c(q)uestion answering) is a ready-to-use model capable of general question answering, showing robustness outside

AI2 430 Jan 04, 2023
Create and implement a deep learning library from scratch.

In this project, we create and implement a deep learning library from scratch. Table of Contents Deep Leaning Library Table of Contents About The Proj

Rishabh Bali 22 Aug 23, 2022
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens

TensorLayer Community 7.1k Dec 27, 2022
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Pytorch Lightning 21.1k Jan 01, 2023