Residual Non-local Attention Networks for Image Restoration

ICLR 2019 Yulun ZhangKunpeng LiKai LiBineng ZhongYun Fu

In this paper, we propose a residual non-local attention network for high-quality image restoration. Without considering the uneven distribution of information in the corrupted images, previous methods are restricted by local convolutional operation and equal treatment of spatial- and channel-wise features... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.