Jpeg Compression Artifact Reduction

5 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

Deep Image Prior

DmitryUlyanov/deep-image-prior CVPR 2018

In this paper, we show that, on the contrary, the structure of a generator network is sufficient to capture a great deal of low-level image statistics prior to any learning.

SwinIR: Image Restoration Using Swin Transformer

jingyunliang/swinir 23 Aug 2021

In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection.

Accurate Image Restoration with Attention Retractable Transformer

gladzhang/art 4 Oct 2022

This is considered as a dense attention strategy since the interactions of tokens are restrained in dense regions.

CUR Transformer: A Convolutional Unbiased Regional Transformer for Image Denoising

2023-MindSpore-1/ms-code-79 journal 2023

Based on the prior that, for each pixel, its similar pixels are usually spatially close, our insights are that (1) we partition the image into non-overlapped windows and perform regional self-attention to reduce the search range of each pixel, and (2) we encourage pixels across different windows to communicate with each other.