Unconditional Image Generation

12 papers with code • 3 benchmarks • 1 datasets

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Datasets


Greatest papers with code

AutoGAN: Neural Architecture Search for Generative Adversarial Networks

VITA-Group/AutoGAN ICCV 2019

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

Image Classification Image Generation +2

Instance-Conditioned GAN

facebookresearch/ic_gan 10 Sep 2021

Generative Adversarial Networks (GANs) can generate near photo realistic images in narrow domains such as human faces.

Conditional Image Generation Unconditional Image Generation

Score-Based Generative Modeling through Stochastic Differential Equations

yang-song/score_sde ICLR 2021

Combined with multiple architectural improvements, we achieve record-breaking performance for unconditional image generation on CIFAR-10 with an Inception score of 9. 89 and FID of 2. 20, a competitive likelihood of 2. 99 bits/dim, and demonstrate high fidelity generation of 1024 x 1024 images for the first time from a score-based generative model.

Colorization Image Inpainting +1

AdversarialNAS: Adversarial Neural Architecture Search for GANs

chengaopro/AdversarialNAS CVPR 2020

In this paper, we propose an AdversarialNAS method specially tailored for Generative Adversarial Networks (GANs) to search for a superior generative model on the task of unconditional image generation.

Image Generation Neural Architecture Search +1

ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models

jychoi118/ilvr_adm ICCV 2021

In this work, we propose Iterative Latent Variable Refinement (ILVR), a method to guide the generative process in DDPM to generate high-quality images based on a given reference image.

Denoising Image Generation +2

Learning Semantic-aware Normalization for Generative Adversarial Networks

researchmm/SariGAN NeurIPS 2020

Such a model disentangles latent factors according to the semantic of feature channels by channel-/group- wise fusion of latent codes and feature channels.

Image Inpainting Unconditional Image Generation

Manifold Matching via Deep Metric Learning for Generative Modeling

dzld00/pytorch-manifold-matching ICCV 2021

We propose a manifold matching approach to generative models which includes a distribution generator (or data generator) and a metric generator.

Image Generation Metric Learning +2

Large Scale Adversarial Representation Learning

lukemelas/unsupervised-image-segmentation NeurIPS 2019

We extensively evaluate the representation learning and generation capabilities of these BigBiGAN models, demonstrating that these generation-based models achieve the state of the art in unsupervised representation learning on ImageNet, as well as in unconditional image generation.

Image Generation Self-Supervised Image Classification +3

Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs

a514514772/hijackgan CVPR 2021

While Generative Adversarial Networks (GANs) show increasing performance and the level of realism is becoming indistinguishable from natural images, this also comes with high demands on data and computation.

Image Generation Unconditional Image Generation

Non-Adversarial Image Synthesis with Generative Latent Nearest Neighbors

yedidh/glann CVPR 2019

GLANN combines the strengths of IMLE and GLO in a way that overcomes the main drawbacks of each method.

Image Generation Unconditional Image Generation