83 datasets found

The MAGIC dataset is a multiclass classification dataset containing 19020 samples, each described by 10 features.

Relational CLEVR is a synthetic dataset of rendered 3D objects of various colours, shapes, sizes and textures.

Positional CLEVR is a synthetic dataset of rendered 3D objects of various colours, shapes, sizes and textures.

Generative Adversarial Networks (GANs) have a great performance in image generation, but they need a large scale of data to train the entire framework, and often result in...

The authors used a dataset of 1000 images, each consisting of three randomly selected MNIST digits.

The dataset used in this paper for image generation.

The dataset used for training the diffusion model, containing 2M images.

Diffusion models have attracted significant attention due to the remarkable ability to create content and generate data for tasks like image classification. However, the usage...

The dataset contains images of subjects and styles, used for training and testing the FreeTuner model.

FreeTuner is a training-free method for compositional personalization that can generate any user-provided subject in any user-provided style.

Text-to-image Latent Diffusion model, CLIP model, Blended Diffusion model, GLIDE model, GLIDE-filtered model

Diffusion Models (DMs) represent a powerful class of generative models that have gained significant attention in recent years.

The Flintstones dataset is a story visualization dataset used in this paper. It contains a story visualization task that is similar to the Pororo-SV dataset.

Story visualization aims to generate a sequence of images to narrate each sentence in a multi-sentence story, where the images should be realistic and keep global consistency...

The LLD-logo dataset is a subset of the LLD dataset, containing 122,920 logos in 400x400 pixel resolution.

The LLD-icon dataset is a subset of the LLD dataset, containing 486,377 logos in 32x32 pixel resolution.

The Large Logo Dataset (LLD) is a large-scale logo dataset crawled from the web, containing 486,377 logos in 32x32 pixel resolution.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the ImageNet, ImageNetV2, ImageNet-Sketch, ImageNet-A, and Imagenet-R datasets.

The dataset used in this paper is the FashionMNIST dataset, which consists of 60,000 images of clothing items from 10 different classes.

A dataset of over 60,000 customized diffusion model weights, each fine-tuned to insert a different person's visual identity.