14 citations · 15 across the 6 of their papers we have counts for
4 papers · 1 filter
DeepRFTv2: Kernel-level Learning for Image Deblurring
Xintian Mao, Haofei Song, Yin-Nian Liu +2
It is well-known that if a network aims to learn how to deblur, it should understand the blur process. Blurring is naturally caused by the convolution of the sharp image with the b…
LoFormer: Local Frequency Transformer for Image Deblurring
Xintian Mao, Jiansheng Wang, Xingran Xie +2
Due to the computational complexity of self-attention (SA), prevalent techniques for image deblurring often resort to either adopting localized SA or employing coarse-grained globa…
AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurring
Xintian Mao, Qingli Li, Yan Wang
Despite the recent progress in enhancing the efficacy of image deblurring, the limited decoding capability constrains the upper limit of State-Of-The-Art (SOTA) methods. This paper…
Intriguing Findings of Frequency Selection for Image Deblurring
Xintian Mao, Yiming Liu, Fengze Liu +3
Blur was naturally analyzed in the frequency domain, by estimating the latent sharp image and the blur kernel given a blurry image. Recent progress on image deblurring always desig…