Audio / Image / Video Generation

Published: 09 Oct 2015 Category: deep_learning


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

Statistics of Deep Generated Images

Sketch-to-Image Generation Using Deep Contextual Completion

Energy-relaxed Wassertein GANs(EnergyWGAN): Towards More Stable and High Resolution Image Generation

Spatial PixelCNN: Generating Images from Patches

Visual to Sound: Generating Natural Sound for Videos in the Wild

Semi-supervised FusedGAN for Conditional Image Generation

Image Transformer

Unpaired Multi-Domain Image Generation via Regularized Conditional GANs

Transferring GANs: generating images from limited data

Cross Domain Image Generation through Latent Space Exploration with Adversarial Loss

Face Image Generation

Fader Networks: Manipulating Images by Sliding Attributes

Person Image Generation

Disentangled Person Image Generation

Pose Guided Person Image Generation

Deformable GANs for Pose-based Human Image Generation

Unpaired Pose Guided Human Image Generation

Video Generation

MoCoGAN: Decomposing Motion and Content for Video Generation

Attentive Semantic Video Generation using Captions

Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture

Towards an Understanding of Our World by GANing Videos in the Wild

Video Generation from Single Semantic Label Map

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


Torch convolutional GAN: Generating Faces with Torch

Generating Large Images from Latent Vectors

Generating Faces with Deconvolution Networks

Attention Models in Image and Caption Generation

Deconvolution and Checkerboard Artifacts


Generate cat images with neural networks


  • 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:

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