44 citations · 50 across the 6 of their papers we have counts for
6 papers
PanFlowNet: A Flow-Based Deep Network for Pan-sharpening
Gang Yang, Xiangyong Cao, Wenzhe Xiao +4
Pan-sharpening aims to generate a high-resolution multispectral (HRMS) image by integrating the spectral information of a low-resolution multispectral (LRMS) image with the texture…
Random Weights Networks Work as Loss Prior Constraint for Image Restoration
Man Zhou, Naishan Zheng, Jie Huang +5
In this paper, orthogonal to the existing data and model studies, we instead resort our efforts to investigate the potential of loss function in a new perspective and present our b…
Unlocking Masked Autoencoders as Loss Function for Image and Video Restoration
Man Zhou, Naishan Zheng, Jie Huang +2
Image and video restoration has achieved a remarkable leap with the advent of deep learning. The success of deep learning paradigm lies in three key components: data, model, and lo…
Probability-based Global Cross-modal Upsampling for Pansharpening
Zeyu Zhu, Xiangyong Cao, Man Zhou +2
Pansharpening is an essential preprocessing step for remote sensing image processing. Although deep learning (DL) approaches performed well on this task, current upsampling methods…
Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement
Chongyi Li, Chun-Le Guo, Man Zhou +4
Ultra-High-Definition (UHD) photo has gradually become the standard configuration in advanced imaging devices. The new standard unveils many issues in existing approaches for low-l…
Source-Free Domain Adaptation for Real-world Image Dehazing
Hu Yu, Jie Huang, Yajing Liu +3
Deep learning-based source dehazing methods trained on synthetic datasets have achieved remarkable performance but suffer from dramatic performance degradation on real hazy images…