9.2k citations · 12.1k across the 87 of their papers we have counts for
11 papers · 1 filter
Local Patch Network with Global Attention for Infrared Small Target Detection
Fang Chen, Chenqiang Gao, Fangcen Liu +4
Infrared small target detection plays an important role in the infrared search and tracking applications. In recent years, deep learning techniques were introduced to this task and…
Infrared Small-Dim Target Detection with Transformer under Complex Backgrounds
Fangcen Liu, Chenqiang Gao, Fang Chen +3
The infrared small-dim target detection is one of the key techniques in the infrared search and tracking system. Since the local regions similar to infrared small-dim targets sprea…
Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions
Qi Xie, Qian Zhao, Zongben Xu +1
It has been shown that equivariant convolution is very helpful for many types of computer vision tasks. Recently, the 2D filter parametrization technique plays an important role wh…
RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining
Hong Wang, Qi Xie, Qian Zhao +4
As a common weather, rain streaks adversely degrade the image quality. Hence, removing rains from an image has become an important issue in the field. To handle such an ill-posed s…
Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks
Jun Shu, Deyu Meng, Zongben Xu
Meta learning has attracted much attention recently in machine learning community. Contrary to conventional machine learning aiming to learn inherent prediction rules to predict la…
Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel
Zongsheng Yue, Qian Zhao, Jianwen Xie +3
While researches on model-based blind single image super-resolution (SISR) have achieved tremendous successes recently, most of them do not consider the image degradation sufficien…
A Deep Variational Bayesian Framework for Blind Image Deblurring
Hui Wang, Zongsheng Yue, Qian Zhao +1
Blind image deblurring is an important yet very challenging problem in low-level vision. Traditional optimization based methods generally formulate this task as a maximum-a-posteri…
EPSANet: An Efficient Pyramid Squeeze Attention Block on Convolutional Neural Network
Hu Zhang, Keke Zu, Jian Lu +2
Recently, it has been demonstrated that the performance of a deep convolutional neural network can be effectively improved by embedding an attention module into it. In this work, a…
Semi-Supervised Video Deraining with Dynamical Rain Generator
Zongsheng Yue, Jianwen Xie, Qian Zhao +1
While deep learning (DL)-based video deraining methods have achieved significant success recently, they still exist two major drawbacks. Firstly, most of them do not sufficiently m…
Stein variational gradient descent on infinite-dimensional space and applications to statistical inverse problems
Junxiong Jia, Peijun Li, Deyu Meng
In this paper, we propose an infinite-dimensional version of the Stein variational gradient descent (iSVGD) method for solving Bayesian inverse problems. The method can generate ap…
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond
Risheng Liu, Jiaxin Gao, Jin Zhang +2
Bi-Level Optimization (BLO) is originated from the area of economic game theory and then introduced into the optimization community. BLO is able to handle problems with a hierarchi…