150 citations · 583 across the 49 of their papers we have counts for
12 papers · 1 filter
A^2Net: Adjacent Aggregation Networks for Image Raindrop Removal
Huangxing Lin, Xueyang Fu, Changxing Jing +2
Existing methods for single images raindrop removal either have poor robustness or suffer from parameter burdens. In this paper, we propose a new Adjacent Aggregation Network (A^2N…
A Deep Tree-Structured Fusion Model for Single Image Deraining
Xueyang Fu, Qi Qi, Yue Huang +3
We propose a simple yet effective deep tree-structured fusion model based on feature aggregation for the deraining problem. We argue that by effectively aggregating features, a rel…
Progressive Feature Alignment for Unsupervised Domain Adaptation
Chaoqi Chen, Weiping Xie, Wenbing Huang +5
Unsupervised domain adaptation (UDA) transfers knowledge from a label-rich source domain to a fully-unlabeled target domain. To tackle this task, recent approaches resort to discri…
An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection
Liyan Sun, Jiexiang Wang, Yue Huang +3
The identification of lesion within medical image data is necessary for diagnosis, treatment and prognosis. Segmentation and classification approaches are mainly based on supervise…
Lightweight Pyramid Networks for Image Deraining
Xueyang Fu, Borong Liang, Yue Huang +2
Existing deep convolutional neural networks have found major success in image deraining, but at the expense of an enormous number of parameters. This limits their potential applica…
A Deeply-Recursive Convolutional Network for Crowd Counting
Xinghao Ding, Zhirui Lin, Fujin He +2
The estimation of crowd count in images has a wide range of applications such as video surveillance, traffic monitoring, public safety and urban planning. Recently, the convolution…
Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network
Liyan Sun, Zhiwen Fan, Yue Huang +2
The need for fast acquisition and automatic analysis of MRI data is growing in the age of big data. Although compressed sensing magnetic resonance imaging (CS-MRI) has been studied…
Residual-Guide Feature Fusion Network for Single Image Deraining
Zhiwen Fan, Huafeng Wu, Xueyang Fu +2
Single image rain streaks removal is extremely important since rainy images adversely affect many computer vision systems. Deep learning based methods have found great success in i…
A Deep Information Sharing Network for Multi-contrast Compressed Sensing MRI Reconstruction
Liyan Sun, Zhiwen Fan, Yue Huang +2
In multi-contrast magnetic resonance imaging (MRI), compressed sensing theory can accelerate imaging by sampling fewer measurements within each contrast. The conventional optimizat…
A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI
Zhiwen Fan, Liyan Sun, Xinghao Ding +3
Compressed sensing MRI is a classic inverse problem in the field of computational imaging, accelerating the MR imaging by measuring less k-space data. The deep neural network model…
A Divide-and-Conquer Approach to Compressed Sensing MRI
Liyan Sun, Zhiwen Fan, Xinghao Ding +3
Compressed sensing (CS) theory assures us that we can accurately reconstruct magnetic resonance images using fewer k-space measurements than the Nyquist sampling rate requires. In…
A Deep Error Correction Network for Compressed Sensing MRI
Liyan Sun, Zhiwen Fan, Yue Huang +2
Compressed sensing for magnetic resonance imaging (CS-MRI) exploits image sparsity properties to reconstruct MRI from very few Fourier k-space measurements. The goal is to minimize…