27 datasets found

The dataset used in the paper is a combination of the CLIC intra coding challenge 2021, the TECNICK dataset, and the DIV2K dataset.

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 dataset used in this paper is the BSDS500 dataset, which contains 200 natural images with over 1000 ground truth labellings.

The proposed framework generates JPEG compressed images using generative adversarial networks.

Malaria Cell Images Dataset

The dataset used in the paper is the CLIC Compression Challenge Professional Dataset.

KITTI Stereo 2012 and 2015 dataset.

Neural distributed image compression using common information.

Deep image compression using decoder side information.

The dataset used in the paper is the CLIC2020 test dataset and the Kodak dataset.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used Kodak, Tecnick, and CLIC 2022 as their test sets.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used Flicker2W and LIU4K as their training sets.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors tested their model on various signal reconstruction tasks: 1D sinusoidal...

CLIC 2019 Professional dataset

Variable rate deep image compression with modulated autoencoder

The dataset used in the paper is the Kodak PhotoCD dataset, which contains twenty-four 768 × 512 images.

The dataset is a collection of 256x256 pixel images.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the OpenImages dataset to train their models.

The proposed system is composed of three neural networks (NN): an auto-regressive module (ARM) fψ, an upsampler fυ and a synthesis fθ.