Browse > Computer Vision > Image Generation

Image Generation

198 papers with code · Computer Vision

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

  • Unconditional generation refers to generating samples unconditionally from the dataset, i.e. $p(y)$
  • Conditional image generation (subtask) refers to generating samples conditionally from the dataset, based on a label, i.e. $p(y|x)$.

In this section, you can find state-of-the-art leaderboards for unconditional generation. For conditional generation, and other types of image generations, refer to the subtasks.

State-of-the-art leaderboards

Latest papers with code

AutoGAN: Neural Architecture Search for Generative Adversarial Networks

11 Aug 2019TAMU-VITA/AutoGAN

Neural architecture search (NAS) has witnessed prevailing success in image classification and (very recently) segmentation tasks.

IMAGE CLASSIFICATION IMAGE GENERATION NEURAL ARCHITECTURE SEARCH

98
11 Aug 2019

SynthText3D: Synthesizing Scene Text Images from 3D Virtual Worlds

13 Jul 2019MhLiao/SynthText3D

Different from the previous methods which paste the rendered text on static 2D images, our method can render the 3D virtual scene and text instances as an entirety.

IMAGE GENERATION SCENE TEXT DETECTION

45
13 Jul 2019

Generative Modeling by Estimating Gradients of the Data Distribution

12 Jul 2019ermongroup/ncsn

We introduce a new generative model where samples are produced via Langevin dynamics using gradients of the data distribution estimated with score matching.

IMAGE GENERATION IMAGE INPAINTING

106
12 Jul 2019

Mean Spectral Normalization of Deep Neural Networks for Embedded Automation

9 Jul 2019AntixK/mean_spectral_norm

Deep Neural Networks (DNNs) have begun to thrive in the field of automation systems, owing to the recent advancements in standardising various aspects such as architecture, optimization techniques, and regularization.

IMAGE GENERATION

7
09 Jul 2019

Guided Image Generation with Conditional Invertible Neural Networks

4 Jul 2019VLL-HD/FrEIA

We demonstrate these properties for the tasks of MNIST digit generation and image colorization.

COLORIZATION IMAGE GENERATION

58
04 Jul 2019

Mask Embedding in conditional GAN for Guided Synthesis of High Resolution Images

3 Jul 2019johnryh/Face_Embedding_GAN

To use semantic masks as guidance whilst providing realistic synthesized results with fine details, we propose to use mask embedding mechanism to allow for a more efficient initial feature projection in the generator.

IMAGE GENERATION

59
03 Jul 2019

Inspirational Adversarial Image Generation

17 Jun 2019facebookresearch/pytorch_GAN_zoo

We design a simple optimization method to find the optimal latent parameters corresponding to the closest generation to any input inspirational image.

IMAGE GENERATION

768
17 Jun 2019

The Implicit Metropolis-Hastings Algorithm

9 Jun 2019necludov/implicit-MH

For any implicit probabilistic model and a target distribution represented by a set of samples, implicit Metropolis-Hastings operates by learning a discriminator to estimate the density-ratio and then generating a chain of samples.

IMAGE GENERATION

1
09 Jun 2019

Image Synthesis with a Single (Robust) Classifier

6 Jun 2019MadryLab/robustness_applications

We show that the basic classification framework alone can be used to tackle some of the most challenging tasks in image synthesis.

IMAGE GENERATION

49
06 Jun 2019

Generative Adversarial Networks: A Survey and Taxonomy

4 Jun 2019sheqi/GAN_Review

We propose loss-variants and architecture-variants for classifying the most popular GANs, and discuss the potential improvements with focusing on these two aspects.

IMAGE-TO-IMAGE TRANSLATION

151
04 Jun 2019