24 datasets found

Emotion diary entries with summarized narratives of emotion, emotions per sentence, and text-to-image prompts.

The dataset used in this paper is a text-to-image diffusion model, specifically Stable Diffusion v1-5.

The dataset used for text-to-image diffusion models, including Bluefire, Paintings, 3D, and Origami styles.

Text-to-image models, such as DDIM or PLMS.

The dataset used in the paper is a collection of images with multiple concepts, where the goal is to disentangle multiple concepts from a single image.

The dataset used in this paper is a large-scale text-to-image diffusion model, which consists of 35 subjects with unique pets and objects.

The dataset used in this paper is a large-scale text-to-image diffusion model, which consists of 35 subjects with unique pets and objects.

Text-to-image dataset with conditional control

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

The image-only stickers dataset used for testing the kNN-Diffusion model.

The dataset used for training the kNN-Diffusion model, which consists of a large-scale retrieval method for training a text-to-image model without any text data.

A large dataset of text-to-image prompts for training and evaluation

MD30 (Manually-annotated Dataset) comprises 30 images chosen from the 807 images. For those images, we discard sn by BLIP2 and attach a more accurate text as sn by a human...

NoiseCollage generates an image with N objects from the following conditions, L, S, and s∗: L = {l1,..., lN } is the N layout conditions to control the layout of individual...

The FFHQ dataset is a large dataset of high-quality face images with 1024 × 1024 resolution with variations in age, gender, and glasses.

The dataset used in the paper is a benchmark dataset created by the authors of the Attend-And-Excite paper.

Moongate dataset consists of images of a moongate.

The CustomConcept101 dataset is a dataset of 101 concepts across 16 broader categories, used for evaluating personalization approaches in text-to-image diffusion models.

The GEMRec-18K dataset contains 18 thousand images generated by 200 text-to-image diffusion models fine-tuned on Stable Diffusion.

The dataset used in the paper is a text-to-image personalization dataset, which consists of 16 concepts and 31 prompts.