Mar 30, 2021 · The purpose of MAM is to effectively enhance the discriminative learning ability of the model with attention mechanisms. In addition, a ...

Abstract. The recent convolutional neural network based studies on the compression artifact reduction (CAR) task have made great progress.

Mar 30, 2021 · Abstract. The recent convolutional neural network based studies on the compression artifact reduction (CAR) task have made great progress.

Progressive multi-scale attention network for compression artifact reduction · Xinyan ZhangPeng GaoGuitao LiL. Yin. Computer Science. J. Electronic Imaging.

Image restoration (IR) tasks aim to form a balance between complex textures and spatial details. To this end, the combination of local and non-local ...

We present a comprehensive study and evaluation of existing single image compression artifact removal algorithms using a new 4K resolution benchmark.

Sep 22, 2022 · Table 1: Quantitative comparison (average PSNR/SSIM) with state-of-the-art methods for JPEG compression artifact reduction on benchmark datasets ...

Compression artifacts removal methods based on convolutional neural networks have attracted great attention. However, most existing methods require a ...

Sep 17, 2022 · This two-stage design effectively selects different exposure values for each input frame and useful information that is not altered by motion ...

An effective scheme that decomposes the image into distinct frequency components, processes them sepa- rately, and recombines the results via a dual attention.