53 datasets found

The dataset used in the paper is a large-scale photo sharing service, where images are stored and retrieved. The authors propose a new recompression technique to reduce storage...

The CLIC2020 professional test dataset provides high-quality images with an average resolution of 1803 x 1175 pixels.

The proposed end-to-end optimized image compression model using the frequency-oriented transform.

A JPEG-like image compression computational experiment is presented.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors trained their model on the CLIC training dataset.

The TECNICK image dataset is a collection of images used for testing image compression algorithms.

The CLIC image dataset is a collection of images used for testing image compression algorithms.

The Kodak PhotoCD image dataset is a collection of images used for testing image compression algorithms.

The proposed JointIQ-Net is a novel end-to-end learning scheme for image compression and quality enhancement.

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

The dataset used in the paper for neural image compression.

The CIC 2020 dataset is a collection of images with different compression methods.

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.

Over-fitting based image compression requires weights compactness for compression and fast convergence for practical use, posing challenges for deep convolutional neural...

The dataset used in the paper is not explicitly described. However, it is mentioned that the authors used a transformer-masked autoencoder (TMAE) to enhance data compression in...

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

Generative model based image lossless compression algorithms have seen a great success in improving compression ratio. However, the throughput for most of them is less than 1...

The dataset used in the paper for neural joint source-channel coding.