63 datasets found

The Open Image Dataset (OID) is a large-scale image dataset that contains a diverse set of images.

The dataset used for training and testing the proposed Multi-scale Dense Cross Network (MDCN) for image super-resolution.

The proposed End-to-End Deep and Shallow (EEDS) networks method for image super-resolution.

A component divide-and-conquer approach for real-world image super-resolution.

An enhanced super-resolution generative adversarial network.

A benchmark for real-world image super-resolution.

A video compression degradation model to synthesize low-resolution image data in the blind SISR task.

The dataset contains images with varying levels of degradation.

A dataset of images for image super-resolution, including license plate images.

A dataset of images for license plate super-resolution, including images with varying lighting conditions.

A dataset of Saudi license plates, both in low and high resolutions, used for training a diffusion model for license plate super-resolution.

CelebA face dataset for image super-resolution.

The DIV2K 3× dataset is used for training and evaluation of the proposed NCNet model.

Remote sensing images captured by different platforms exhibit significant disparities in spatial resolution. Large scale factor super-resolution (SR) algorithms are vital for...

The CNAM-CD dataset is a multi-class change detection dataset with a resolution of 0.5 meter.

The SECOND dataset is a semantic change detection dataset with 7 land cover class annotations.

Image classification, image super-resolution, and compression artifact reduction tasks

Manga109 dataset is a benchmark for Single Image Super-Resolution (SISR) tasks. It contains 109 manga images with randomly selected reference images.

The Urban100 dataset is a benchmark for image denoising, containing 100 images with varying levels of noise.

The BSD100 dataset consists of 100 images with 4x scaling.