76 datasets found

A dataset for subject-driven generation, containing 30 subjects, including objects and live subjects/pets.

This paper documents our characterization study and practices for serving text-to-image requests with stable diffusion models in production.

A new benchmark for evaluating text-to-image generation models, constructed to analyze semantic issues in text-based image generation.

The dataset used for training and evaluation of the W¨urstchen model.

The dataset used for training and evaluation of the W¨urstchen model.

A large database of 2 million images, which can also be downloaded and used as open source.

The dataset used in the paper is not explicitly described, but it is mentioned that it is a large-scale captioned image dataset (LAION) used to train the Stable Diffusion model.

BLIP-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

The dataset used in the paper is not explicitly mentioned, but it is implied to be a text-to-image dataset.

A dataset for evaluating the performance of text-to-image models, namely ViLG-300 and ParaPrompts-400.

A dataset for evaluating the performance of text-to-image models, namely ViLG-300 and ParaPrompts-400.

A small but high-quality dataset with manual annotations, namely ParaImage-Small, where the corresponding textual descriptions can extend up to 500 words.

A high-quality, textual rich paragraph-to-image pairs dataset, namely ParaImage-Big, where the corresponding textual descriptions can extend up to 400 words.

A high-quality, textual rich paragraph-to-image pairs dataset, namely ParaImage, where the corresponding textual descriptions can extend up to 400 words.

DiffusionDB: A large-scale prompt gallery dataset for text-to-image generative models.

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...