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20122022
most citedBridging Saliency Detection to Weakly Supervised Object Detection Based on Self-paced Curriculum Learning

83 citations · 340 across the 30 of their papers we have counts for

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26 papers · 1 filter

cs.CV20221 cited

KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution

Jiahong Fu, Hong Wang, Qi Xie +3

Although current deep learning-based methods have gained promising performance in the blind single image super-resolution (SISR) task, most of them mainly focus on heuristically co…

cs.CV20224 cited

Low-light Image Enhancement by Retinex Based Algorithm Unrolling and Adjustment

Xinyi Liu, Qi Xie, Qian Zhao +2

Motivated by their recent advances, deep learning techniques have been widely applied to low-light image enhancement (LIE) problem. Among which, Retinex theory based ones, mostly f…

cs.CV2021

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…

cs.CV20214 cited

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…

cs.CV20201 cited

TSGCNet: Discriminative Geometric Feature Learning with Two-Stream GraphConvolutional Network for 3D Dental Model Segmentation

Lingming Zhang, Yue Zhao, Deyu Meng +5

The ability to segment teeth precisely from digitized 3D dental models is an essential task in computer-aided orthodontic surgical planning. To date, deep learning based methods ha…

cs.CV20201 cited

Unsupervised Learning of Local Discriminative Representation for Medical Images

Huai Chen, Jieyu Li, Renzhen Wang +5

Local discriminative representation is needed in many medical image analysis tasks such as identifying sub-types of lesion or segmenting detailed components of anatomical structure…