88 datasets found

The HEE model uses CIFAR10 to demonstrate its ability to generate high-quality images.

MNIST and celebA datasets were used to train and evaluate the proposed QDCGAN architecture.

The authors used MNIST and CelebA datasets for their experiments.

Synthetic data from diffusion models augmenting real-world data

Generated ImageNet-100 data for training ResNet-18

The dataset used in the paper is a toy dataset consisting of 2D images.

The dataset used in the paper is a Anime128x128 dataset.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the LSUN-Church and LSUN-Bedroom datasets.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the DDIM diffusion model and the LDMs diffusion model.

StyleFusion: A Generative Model for Disentangling Spatial Segments

Visual ChatGPT is a system that integrates different Visual Foundation Models to understand visual information and generation corresponding answers.

TU-Berlin sketch dataset.

The dataset used in the paper is a collection of high-quality graphic design images.

The DESIGNERINTENTION benchmark consists of approximately 500 graphic design intention prompts.

ImageNet [9] and CC-3M [43] datasets

LSUN-{cat, bedroom, church} [48] and FFHQ [25] datasets

The Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix dataset contains 4870 registered image pairs, covering a variety of HER2 expression levels.

Open-vocabulary Responsible Visual Synthesis (ORES) aims to generate an image under the user's query u that meets two criteria: 1) it should not contain a specified visual...

The dataset used in the paper for training and testing the Denoising Diffusion Implicit Models.

The dataset used in this paper is a diffusion model for image generation.