97 citations · 290 across the 24 of their papers we have counts for
25 papers
Asymptotic behaviour for escaping an interval by Lévy flights under stochastic resetting
Bartosz Zbik, Zbigniew Palmowski
The resetting of stochastic processes has become a key mechanism appearing in many research fields, such as searching for a target, the transmission control protocol, biology, chem…
Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction
Miaoyu Li, Ying Fu, Ji Liu +1
Hyperspectral Image (HSI) reconstruction has made gratifying progress with the deep unfolding framework by formulating the problem into a data module and a prior module. Neverthele…
Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising
Miaoyu Li, Ji Liu, Ying Fu +2
Denoising is a crucial step for hyperspectral image (HSI) applications. Though witnessing the great power of deep learning, existing HSI denoising methods suffer from limitations i…
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising
Zichun Wang, Ying Fu, Ji Liu +1
Despite the significant results on synthetic noise under simplified assumptions, most self-supervised denoising methods fail under real noise due to the strong spatial noise correl…
Instance Segmentation in the Dark
Linwei Chen, Ying Fu, Kaixuan Wei +2
Existing instance segmentation techniques are primarily tailored for high-visibility inputs, but their performance significantly deteriorates in extremely low-light environments. I…
Hybrid Spectral Denoising Transformer with Guided Attention
Zeqiang Lai, Chenggang Yan, Ying Fu
In this paper, we present a Hybrid Spectral Denoising Transformer (HSDT) for hyperspectral image denoising. Challenges in adapting transformer for HSI arise from the capabilities t…
Mixed Attention Network for Hyperspectral Image Denoising
Zeqiang Lai, Ying Fu
Hyperspectral image denoising is unique for the highly similar and correlated spectral information that should be properly considered. However, existing methods show limitations in…
Spatial-Spectral Transformer for Hyperspectral Image Denoising
Miaoyu Li, Ying Fu, Yulun Zhang
Hyperspectral image (HSI) denoising is a crucial preprocessing procedure for the subsequent HSI applications. Unfortunately, though witnessing the development of deep learning in H…
Improved Quasi-Recurrent Neural Network for Hyperspectral Image Denoising
Zeqiang Lai, Ying Fu
Hyperspectral image is unique and useful for its abundant spectral bands, but it subsequently requires extra elaborated treatments of the spatial-spectral correlation as well as th…
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…
ProbNVS: Fast Novel View Synthesis with Learned Probability-Guided Sampling
Yuemei Zhou, Tao Yu, Zerong Zheng +2
Existing state-of-the-art novel view synthesis methods rely on either fairly accurate 3D geometry estimation or sampling of the entire space for neural volumetric rendering, which…
Estimating Fine-Grained Noise Model via Contrastive Learning
Yunhao Zou, Ying Fu
Image denoising has achieved unprecedented progress as great efforts have been made to exploit effective deep denoisers. To improve the denoising performance in realworld, two typi…
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…
LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation
Ruizhi Shao, Gaochang Wu, Yuemei Zhou +2
Cross-resolution image alignment is a key problem in multiscale gigapixel photography, which requires to estimate homography matrix using images with large resolution gap. Existing…
Disentangled Face Attribute Editing via Instance-Aware Latent Space Search
Yuxuan Han, Jiaolong Yang, Ying Fu
Recent works have shown that a rich set of semantic directions exist in the latent space of Generative Adversarial Networks (GANs), which enables various facial attribute editing a…
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…
Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements
Kaixuan Wei, Jiaolong Yang, Ying Fu +2
Removing undesirable reflections from a single image captured through a glass window is of practical importance to visual computing systems. Although state-of-the-art methods can o…