13 datasets found

The CUB dataset is a large collection of images of birds, each image is a 299x299 RGB image, and there are 11,778 training images and 5,994 testing images.

The dataset used in this paper for generative model evaluation, consisting of 4.1M images from 41 state-of-the-art generative models spanning diffusion models, GANs, variational...

Diverse Image Synthesis from Semantic Layouts via Conditional IMLE

A dedicated collection of images: real/pristine images collected from CelebA, FFHQ1, and ImageNet datasets and synthetic data generated by 9 different Generative Adversarial...

Diffusion models have recently emerged as the state-of-the-art of generative modeling, demonstrating remarkable results in image synthesis and across other modalities.

The dataset used in the paper is a set of images from the AFHQ dataset, containing 1.5K images of different animal faces.

ProGAN and LSUN are used as training datasets for the FakeInversion model.

Progress in GANs has enabled the generation of high-res-olution photorealistic images of astonishing quality. StyleGANs allow for compelling attribute modification on such...

The dataset used for calibration during the quantization process.

This dataset is used in the paper to demonstrate the effectiveness of the GANSpace technique.

The dataset used in the paper for training and testing the proposed method for detecting, attributing and localizing GAN generated images.

High-fidelity image synthesis using Generative Adversarial Networks (GANs).

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...