Image Generation

Oct 9, 2015

Papers

Optimizing Neural Networks That Generate Images

Learning to Generate Chairs, Tables and Cars with Convolutional Networks

DRAW: A Recurrent Neural Network For Image Generation

What is DRAW (Deep Recurrent Attentive Writer)?

Colorizing the DRAW Model

Understanding and Implementing Deepmind’s DRAW Model

Generative Image Modeling Using Spatial LSTMs

Conditional generative adversarial nets for convolutional face generation

Generating Images from Captions with Attention

Attribute2Image: Conditional Image Generation from Visual Attributes

Autoencoding beyond pixels using a learned similarity metric

Deep Visual Analogy-Making

Pixel Recurrent Neural Networks

Generating images with recurrent adversarial networks

Pixel-Level Domain Transfer

Generative Adversarial Text to Image Synthesis

Conditional Image Generation with PixelCNN Decoders

Inverting face embeddings with convolutional neural networks

Unsupervised Cross-Domain Image Generation

PixelCNN++: A PixelCNN Implementation with Discretized Logistic Mixture Likelihood and Other Modifications

Generating Interpretable Images with Controllable Structure

Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts

Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space

Image Generation and Editing with Variational Info Generative AdversarialNetworks

DeepFace: Face Generation using Deep Learning

Multi-View Image Generation from a Single-View

Generative Cooperative Net for Image Generation and Data Augmentation

https://arxiv.org/abs/1705.02887

Statistics of Deep Generated Images

https://arxiv.org/abs/1708.02688

Deep Generative Model

Digit Fantasies by a Deep Generative Model

Conditional generative adversarial nets for convolutional face generation

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

Torch convolutional GAN: Generating Faces with Torch

One-Shot Generalization in Deep Generative Models

Generative Image Modeling using Style and Structure Adversarial Networks

Synthesizing Dynamic Textures and Sounds by Spatial-Temporal Generative ConvNet

Synthesizing the preferred inputs for neurons in neural networks via deep generator networks

ArtGAN: Artwork Synthesis with Conditional Categorial GANs

Learning to Generate Chairs with Generative Adversarial Nets

https://arxiv.org/abs/1705.10413

Blogs

Torch convolutional GAN: Generating Faces with Torch

Generating Large Images from Latent Vectors

http://blog.otoro.net/2016/04/01/generating-large-images-from-latent-vectors/

Generating Faces with Deconvolution Networks

Attention Models in Image and Caption Generation

Deconvolution and Checkerboard Artifacts

:star::star::star::star::star:

Projects

Generate cat images with neural networks

TF-VAE-GAN-DRAW

  • intro: A collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).
  • github: https://github.com/ikostrikov/TensorFlow-VAE-GAN-DRAW

Generating Large Images from Latent Vectors

Generating Large Images from Latent Vectors - Part Two

Analyzing 50k fonts using deep neural networks

Generate cat images with neural networks

Generate human faces with neural networks

A TensorFlow implementation of DeepMind’s WaveNet paper