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Computer Science

D-Index
33
Citations
5537
World Ranking
12553
National Ranking
5092

Overview

Jun Xu is affiliated with the University of Utah in the United States and has contributed substantially to research in computer science and engineering, particularly focusing on computer vision and pattern recognition.

Their research spans various subfields including computer vision and pattern recognition, artificial intelligence, media technology, radiology, nuclear medicine and imaging, and biomedical engineering. Their work covers a range of topics such as advanced image processing techniques, image enhancement techniques, image and signal denoising methods, visual attention and saliency detection, advanced image and video retrieval techniques, advanced vision and imaging, and advanced X-ray and CT imaging.

Jun Xu has published extensively, with a notable presence in several prominent venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Medical Imaging

Significant recent papers authored or co-authored by Jun Xu include:

  • "Deep Hough Transform for Semantic Line Detection" (2021), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "CDNet: Complementary Depth Network for RGB-D Salient Object Detection" (2021), published in IEEE Transactions on Image Processing
  • "MobileSal: Extremely Efficient RGB-D Salient Object Detection" (2021), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Conditional Variational Image Deraining" (2020), published in IEEE Transactions on Image Processing
  • "PID Controller-Based Stochastic Optimization Acceleration for Deep Neural Networks" (2020), published in IEEE Transactions on Neural Networks and Learning Systems

Their collaborative work involves frequent co-authorship with colleagues such as Xiantong Zhen, Ming-Ming Cheng, Ling Shao, Yingjun Du, and Dinggang Shen, reflecting ongoing partnerships in advancing their research areas.

Best Publications

  • JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation

    Yu-Huan Wu;Shang-Hua Gao;Jie Mei;Jun Xu

  • STAR: A Structure and Texture Aware Retinex Model

    Jun Xu;Yingkun Hou;Dongwei Ren;Li Liu

  • Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising

    Jun Xu;Lei Zhang;Wangmeng Zuo;David Zhang

  • Bilateral Attention Network for RGB-D Salient Object Detection

    Zhao Zhang;Zheng Lin;Jun Xu;Wen-Da Jin

  • Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising

    Jun Xu;Lei Zhang;David Zhang;Xiangchu Feng

  • A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising

    Jun Xu;Lei Zhang;David Zhang

  • RANet: Ranking Attention Network for Fast Video Object Segmentation

    Ziqin Wang;Jun Xu;Li Liu;Fan Zhu

  • Real-world Noisy Image Denoising: A New Benchmark.

    Jun Xu;Hui Li;Zhetong Liang;David Zhang

  • Deep Hough Transform for Semantic Line Detection.

    Kai Zhao;Qi Han;Chang-Bin Zhang;Jun Xu

  • Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image

    Jun Xu;Yuan Huang;Ming-Ming Cheng;Li Liu

  • NLH: A Blind Pixel-Level Non-Local Method for Real-World Image Denoising

    Yingkun Hou;Jun Xu;Mingxia Liu;Guanghai Liu

  • A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping

    Zhetong Liang;Jun Xu;David Zhang;Zisheng Cao

  • CDNet: Complementary Depth Network for RGB-D Salient Object Detection

    Wen-Da Jin;Jun Xu;Qi Han;Yi Zhang

  • MobileSal: Extremely Efficient RGB-D Salient Object Detection.

    Yu-Huan Wu;Yun Liu;Jun Xu;Jia-Wang Bian

  • Sparse, collaborative, or nonnegative representation: Which helps pattern classification?

    Jun Xu;Wangpeng An;Lei Zhang;David Zhang;David Zhang

  • Noisy-as-Clean: Learning Self-Supervised Denoising From Corrupted Image

    Jun Xu;Yuan Huang;Ming-Ming Cheng;Li Liu

  • External Prior Guided Internal Prior Learning for Real-World Noisy Image Denoising

    Jun Xu;Lei Zhang;David Zhang

  • Learning to Learn with Variational Information Bottleneck for Domain Generalization

    Yingjun Du;Jun Xu;Huan Xiong;Qiang Qiu

  • A PID Controller Approach for Stochastic Optimization of Deep Networks

    Wangpeng An;Wangpeng An;Haoqian Wang;Haoqian Wang;Qingyun Sun;Jun Xu

  • Gradient-Induced Co-Saliency Detection

    Zhao Zhang;Wenda Jin;Jun Xu;Ming-Ming Cheng

  • Temporal Modulation Network for Controllable Space-Time Video Super-Resolution

    Gang Xu;Jun Xu;Zhen Li;Liang Wang

Frequent Co-Authors

Lei Zhang
Lei Zhang Hong Kong Polytechnic University
Ling Shao
Ling Shao Terminus International
David Zhang
David Zhang Chinese University of Hong Kong, Shenzhen
Ming-Ming Cheng
Ming-Ming Cheng Nankai University
Xiantong Zhen
Xiantong Zhen University of Amsterdam
Li Liu
Li Liu Inception Institute of Artificial Intelligence
Wangmeng Zuo
Wangmeng Zuo Harbin Institute of Technology
Cees G. M. Snoek
Cees G. M. Snoek University of Amsterdam
Deng-Ping Fan
Deng-Ping Fan Nankai University
Shuai Li
Shuai Li University of Oulu

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