44 datasets found

A dataset of images used to evaluate the proposed method for reducing visual distraction in images.

SemanticGAN uses a dataset of real images and their corresponding semantic segmentation masks.

DatasetGAN uses a dataset of real images and their corresponding semantic segmentation masks.

EditGAN uses StyleGAN2 as a backbone generative model of images. The dataset used for training the segmentation branch is a dataset of image-segmentation mask pairs.

InstructPix2Pix is a model for image editing tasks, including removing objects from images.

Visual ChatGPT is a system that integrates different Visual Foundation Models to understand visual information and generation corresponding answers.

The dataset used in the paper Harnessing Human Feedback for Instructional Visual Editing (HIVE) for instructional visual editing.

Text-guided image editing using diffusion models

The dataset used in the paper for user-controllable latent code transformation for StyleGAN image layout editing.

The dataset used in the paper for user-controllable latent code transformation for StyleGAN image layout editing.

The zero-shot semantic image editing dataset, which consists of a set of 150 tuples, each containing a source image, a source text, and a target text.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the Stable Diffusion Model (SDM) v1.5.

A benchmark dataset for text-to-image diffusion models.

A novel framework for single-image editing using pre-trained text-to-image diffusion models.

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

The dataset used for training the InstructAny2Pix model, containing 500k instructions with multi-modal inputs.

A dataset comprising 3000 images for quantitative evaluation of specified region customization with both text and image inputs.

Given a short monocular RGB video and text instructions, our method uses an image-conditioned diffusion model to edit one head image and uses the video stylization method to...

The Region-Aware Diffusion for Zero-Shot Text-Driven Image Editing dataset is used to evaluate the ability of models to edit images based on text descriptions.

StyleCLIP-FEU uses FlickrFaces-HQ (FFHQ) as the image corpus I.