Image Generation


Image generation (synthesis) is the task of generating new images from an existing dataset.

Overview

6 GAN Architectures You Really Should Know
Some of the most popular GAN architectures, particularly 6 architectures that you should know to have a diverse coverage on GANs.
generative-adversarial-networks survey tutorial article

Tutorials

Controllable Person Image Synthesis with Attribute-Decomposed GAN
A novel generative model for controllable person image synthesis, which can produce realistic person images with desired human attributes.
generative-adversarial-networks image-synthesis computer-vision pose
Adversarial Latent Autoencoders
Introducing the Adversarial Latent Autoencoder (ALAE), a general architecture that can leverage recent improvements on GAN training procedures.
autoencoders generative-adversarial-networks latent-space disentanglement
GANSpace: Discovering Interpretable GAN Controls
This paper describes a simple technique to analyze Generative Adversarial Networks (GANs) and create interpretable controls for image synthesis.
generative-adversarial-networks image-generation interpretability interpretable-gans
Synthesizing High-Resolution Images with StyleGAN2
Developed by NVIDIA Researchers, StyleGAN2 yields state-of-the-art results in data-driven unconditional generative image modeling.
generative-adversarial-networks stylegan stylegan2 nvidia
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