97 citations · 290 across the 24 of their papers we have counts for
7 papers · 1 filter
Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image
Yuxing Huang, Shaodi You, Ying Fu +1
High-resolution hyperspectral images (HSIs) contain the response of each pixel in different spectral bands, which can be used to effectively distinguish various objects in complex…
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…
Cross-MPI: Cross-scale Stereo for Image Super-Resolution using Multiplane Images
Yuemei Zhou, Gaochang Wu, Ying Fu +2
Various combinations of cameras enrich computational photography, among which reference-based superresolution (RefSR) plays a critical role in multiscale imaging systems. However,…
EasyQuant: Post-training Quantization via Scale Optimization
Di Wu, Qi Tang, Yongle Zhao +3
The 8 bits quantization has been widely applied to accelerate network inference in various deep learning applications. There are two kinds of quantization methods, training-based q…
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 --…
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems
Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang +3
Plug-and-play (PnP) is a non-convex framework that combines ADMM or other proximal algorithms with advanced denoiser priors. Recently, PnP has achieved great empirical success, esp…