70 citations · 104 across the 5 of their papers we have counts for
8 papers
Deep Plug-and-Play Prior for Hyperspectral Image Restoration
Zeqiang Lai, Kaixuan Wei, Ying Fu
Deep-learning-based hyperspectral image (HSI) restoration methods have gained great popularity for their remarkable performance but often demand expensive network retraining whenev…
Physics-based Noise Modeling for Extreme Low-light Photography
Kaixuan Wei, Ying Fu, Yinqiang Zheng +1
Enhancing the visibility in extreme low-light environments is a challenging task. Under nearly lightless condition, existing image denoising methods could easily break down due to…
Dynamic Proximal Unrolling Network for Compressive Imaging
Yixiao Yang, Ran Tao, Kaixuan Wei +1
Compressive imaging aims to recover a latent image from under-sampled measurements, suffering from a serious ill-posed inverse problem. Recently, deep neural networks have been app…
TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems
Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang +3
Plug-and-Play (PnP) is a non-convex optimization framework that combines proximal algorithms, for example, the alternating direction method of multipliers (ADMM), with advanced den…
A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising
Kaixuan Wei, Ying Fu, Jiaolong Yang +1
Lacking rich and realistic data, learned single image denoising algorithms generalize poorly to real raw images that do not resemble the data used for training. Although the proble…
3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising
Kaixuan Wei, Ying Fu, Hua Huang
In this paper, we propose an alternating directional 3D quasi-recurrent neural network for hyperspectral image (HSI) denoising, which can effectively embed the domain knowledge --…