72 datasets found

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.

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

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

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.

The LAION-Aesthetics dataset is a large-scale dataset of images used for training and evaluating computer vision models.

The proposed model is built on the theoretical analysis presented in [30,14]. Similar to the ARAE [14], our model provides flexibility in learning an autoencoder from the input...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the two moons dataset for experiments.

This dataset is used for training and testing the BigGAN model.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors analyzed the generative mechanism of diffusion models and proposed a novel method...

The dataset used for language modeling, disentangled representation learning, and image generation.