44 citations · 131 across the 17 of their papers we have counts for
16 papers · 1 filter
Empowering Low-Light Image Enhancer through Customized Learnable Priors
Naishan Zheng, Man Zhou, Yanmeng Dong +4
Deep neural networks have achieved remarkable progress in enhancing low-light images by improving their brightness and eliminating noise. However, most existing methods construct e…
Learned Image Reasoning Prior Penetrates Deep Unfolding Network for Panchromatic and Multi-Spectral Image Fusion
Man Zhou, Jie Huang, Naishan Zheng +1
The success of deep neural networks for pan-sharpening is commonly in a form of black box, lacking transparency and interpretability. To alleviate this issue, we propose a novel mo…
Generalized Lightness Adaptation with Channel Selective Normalization
Mingde Yao, Jie Huang, Xin Jin +4
Lightness adaptation is vital to the success of image processing to avoid unexpected visual deterioration, which covers multiple aspects, e.g., low-light image enhancement, image r…
High-quality Image Dehazing with Diffusion Model
Hu Yu, Jie Huang, Kaiwen Zheng +1
Image dehazing is quite challenging in dense-haze scenarios, where quite less original information remains in the hazy image. Though previous methods have made marvelous progress,…
Decomposition Ascribed Synergistic Learning for Unified Image Restoration
Jinghao Zhang, Feng Zhao
Learning to restore multiple image degradations within a single model is quite beneficial for real-world applications. Nevertheless, existing works typically concentrate on regardi…
Region-Aware Portrait Retouching with Sparse Interactive Guidance
Huimin Zeng, Jie Huang, Jiacheng Li +1
Portrait retouching aims to improve the aesthetic quality of input portrait photos and especially requires human-region priority. The deep learning-based methods largely elevate th…
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…
Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network
Keyu Yan, Man Zhou, Jie Huang +4
Panchromatic (PAN) and multi-spectral (MS) image fusion, named Pan-sharpening, refers to super-resolve the low-resolution (LR) multi-spectral (MS) images in the spatial domain to g…
Deep Fourier Up-Sampling
Man Zhou, Hu Yu, Jie Huang +5
Existing convolutional neural networks widely adopt spatial down-/up-sampling for multi-scale modeling. However, spatial up-sampling operators (\emph{e.g.}, interpolation, transpos…
CNSNet: A Cleanness-Navigated-Shadow Network for Shadow Removal
Qianhao Yu, Naishan Zheng, Jie Huang +1
The key to shadow removal is recovering the contents of the shadow regions with the guidance of the non-shadow regions. Due to the inadequate long-range modeling, the CNN-based app…
Enhancement by Your Aesthetic: An Intelligible Unsupervised Personalized Enhancer for Low-Light Images
Naishan Zheng, Jie Huang, Qi Zhu +3
Low-light image enhancement is an inherently subjective process whose targets vary with the user's aesthetic. Motivated by this, several personalized enhancement methods have been…
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…
EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration
Ruikang Xu, Zeyu Xiao, Jie Huang +2
Image deblurring has seen a great improvement with the development of deep neural networks. In practice, however, blurry images often suffer from additional degradations such as do…
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
Andrey Ignatov, Radu Timofte, Thang Van Vu +45
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones. The challenge consisted of two tra…
Video-based Sign Language Recognition without Temporal Segmentation
Jie Huang, Wengang Zhou, Qilin Zhang +2
Millions of hearing impaired people around the world routinely use some variants of sign languages to communicate, thus the automatic translation of a sign language is meaningful a…