83 datasets found

The dataset used in the paper is a large dataset of images, including FFHQ, AFHQ-Cat, and LSUN-Church.

Cross-modal datasets with text descriptions for cross-modal image generation under various layout conditions.

VisionLLaMA is a unified and generic modeling framework for solving most vision tasks.

Face stylization refers to the transformation of a face into a specific portrait style. However, current methods require the use of example-based adaptation approaches to...

The dataset used for testing the Concept Sliders, consisting of paired image data and text prompts.

The dataset used for training the Concept Sliders, consisting of paired image data and text prompts.

A multiple relations scene graph-image paired dataset with highly precise labels called MultiRels.

Recently, with the rapid development of artificial intelligence, image generation based on deep learning has advanced significantly. Image generation based on Generative...

Multimodal models trained on large natural image-text pair datasets have exhibited astounding abilities in gener-ating high-quality images. Medical imaging data is fundamentally...

The dataset used in the paper is LAION-2B, which is a large-scale image-text dataset. The authors fine-tune a pre-trained diffusion model with a subset of LAION-2B with 10k...

Human pose transfer, as a misaligned image generation task, is very challenging. Existing methods cannot effectively utilize the input information, which often fail to preserve...

We present FIT: a transformer-based architecture with efficient self-attention and adaptive computation.

ControlNet dataset for image generation

DiffuGen generates high-quality labeled image datasets using stable diffusion models.

The dataset is used for image generation and editing tasks.

The dataset is a 4-way array of dimensions 4000 × 90 × 90 × 3, where each pixel gives the intensity for colors red, green and blue, resulting in a multiway array of dimensions X...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a dataset to train and fine-tune the diffusion model.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a dataset to train and fine-tune the diffusion model.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a dataset to train and fine-tune the diffusion model.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a dataset to train and fine-tune the diffusion model.