World's Best Scientists 2026 revealed!
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Xin Fan

D-Index & Metrics

Computer Science

D-Index
49
Citations
11353
World Ranking
5824
National Ranking
769

Xin Fan publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Xin Fan sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 250 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 560 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 331 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Xin Fan D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Xin Fan sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Xin Fan is affiliated with Dalian University of Technology in China and has contributed extensively to research in the fields of Computer Science and Engineering. Their primary focus lies within the domains of Computer Vision and Pattern Recognition, Media Technology, Biomedical Engineering, Artificial Intelligence, and Civil and Structural Engineering.

The scientist's research covers a range of topics including Image Enhancement Techniques, Advanced Image Fusion Techniques, Advanced Image Processing Techniques, Advanced Vision and Imaging, Advanced Neural Network Applications, Visual Attention and Saliency Detection, and Advanced Image and Video Retrieval Techniques.

Xin Fan has published numerous papers in prominent venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Neurocomputing

Some notable papers by Xin Fan are:

  • Toward Fast, Flexible, and Robust Low-Light Image Enhancement, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Real-World Underwater Enhancement: Challenges, Benchmarks, and Solutions Under Natural Light, 2020, IEEE Transactions on Circuits and Systems for Video Technology
  • Learning a Deep Multi-Scale Feature Ensemble and an Edge-Attention Guidance for Image Fusion, 2021, IEEE Transactions on Circuits and Systems for Video Technology
  • Twin Adversarial Contrastive Learning for Underwater Image Enhancement and Beyond, 2022, IEEE Transactions on Image Processing

Frequent collaborators in Xin Fan's work include Risheng Liu, Zhongxuan Luo, Jinyuan Liu, Long Ma, and Zhiying Jiang.

Best Publications

  • Toward Fast, Flexible, and Robust Low-Light Image Enhancement

    Unknown

  • Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection

    Unknown

  • Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement

    Risheng Liu;Long Ma;Jiaao Zhang;Xin Fan

  • Real-World Underwater Enhancement: Challenges, Benchmarks, and Solutions Under Natural Light

    Risheng Liu;Xin Fan;Ming Zhu;Minjun Hou

  • Twin Adversarial Contrastive Learning for Underwater Image Enhancement and Beyond

    Unknown

  • Quantifying interface and bulk contributions to spin–orbit torque in magnetic bilayers

    Xin Fan;Halise Celik;Jun Wu;Chaoying Ni

  • Learning a Deep Multi-scale Feature Ensemble and an Edge-attention Guidance for Image Fusion

    Jinyuan Liu;Xin Fan;Ji Jiang;Risheng Liu

  • Target Oriented Perceptual Adversarial Fusion Network for Underwater Image Enhancement

    Unknown

  • Accurate Monocular 3D Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving

    Xinzhu Ma;Zhihui Wang;Haojie Li;Pengbo Zhang

  • Unsupervised Misaligned Infrared and Visible Image Fusion via Cross-Modality Image Generation and Registration

    Unknown

  • Super-resolution of human face image using canonical correlation analysis

    Hua Huang;Huiting He;Xin Fan;Junping Zhang

  • Rethinking general underwater object detection: Datasets, challenges, and solutions

    Unknown

  • Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation

    Unknown

  • Attention-Guided Global-Local Adversarial Learning for Detail-Preserving Multi-Exposure Image Fusion

    Unknown

  • Feature selection for imbalanced data based on neighborhood rough sets

    Hongmei Chen;Tianrui Li;Xin Fan;Chuan Luo

  • Anomalous spin-orbit torques in magnetic single-layer films.

    Wenrui Wang;Tao Wang;Vivek P. Amin;Vivek P. Amin;Yang Wang

  • An Interactively Reinforced Paradigm for Joint Infrared-Visible Image Fusion and Saliency Object Detection

    Unknown

  • White Matter Changes in Healthy Adolescents at Familial Risk for Unipolar Depression: A Diffusion Tensor Imaging Study

    Hao Huang;Xin Fan;Douglas E. Williamson;Uma Rao

  • HoLoCo: Holistic and local contrastive learning network for multi-exposure image fusion

    Unknown

  • ReCoNet: Recurrent Correction Network for Fast and Efficient Multi-modality Image Fusion

    Unknown

  • A Bilevel Integrated Model With Data-Driven Layer Ensemble for Multi-Modality Image Fusion

    Risheng Liu;Jinyuan Liu;Zhiying Jiang;Xin Fan

  • Leveraging Line-point Consistence to Preserve Structures for Wide Parallax Image Stitching

    Qi Jia;ZhengJun Li;Xin Fan;Haotian Zhao

  • Learning Deep Context-Sensitive Decomposition for Low-Light Image Enhancement.

    Long Ma;Risheng Liu;Jiaao Zhang;Xin Fan

  • Learning Aggregated Transmission Propagation Networks for Haze Removal and Beyond

    Risheng Liu;Xin Fan;Minjun Hou;Zhiying Jiang

  • Joint Residual Learning for Underwater Image Enhancement

    Minjun Hou;Risheng Liu;Xin Fan;Zhongxuan Luo

  • A Dataset and Benchmark of Underwater Object Detection for Robot Picking

    Chongwei Liu;Haojie Li;Shuchang Wang;Ming Zhu

  • Deep Joint Depth Estimation and Color Correction From Monocular Underwater Images Based on Unsupervised Adaptation Networks

    Xinchen Ye;Zheng Li;Baoli Sun;Zhihui Wang

  • A Fast Ellipse Detector Using Projective Invariant Pruning

    Qi Jia;Xin Fan;Zhongxuan Luo;Lianbo Song

  • Graphical Models for Joint Segmentation and Recognition of License Plate Characters

    Xin Fan;Guoliang Fan

  • On the Convergence of Learning-Based Iterative Methods for Nonconvex Inverse Problems

    Risheng Liu;Shichao Cheng;Yi He;Xin Fan

  • Real-time evolution of tunneling magnetoresistance during annealing in CoFeB∕MgO∕CoFeB magnetic tunnel junctions

    W. G. Wang;C. Ni;A. Rumaiz;Y. Wang

  • Two-Layer Gaussian Process Regression With Example Selection for Image Dehazing

    Xin Fan;Yi Wang;Xianxuan Tang;Renjie Gao

  • Real-world Underwater Enhancement: Challenges, Benchmarks, and Solutions

    Risheng Liu;Xin Fan;Ming Zhu;Minjun Hou

Frequent Co-Authors

Risheng Liu
Risheng Liu Dalian University of Technology
Zhongxuan Luo
Zhongxuan Luo Dalian University of Technology
John Q. Xiao
John Q. Xiao University of Delaware
Huaiwu Zhang
Huaiwu Zhang University of Electronic Science and Technology of China
Chaoying Ni
Chaoying Ni University of Delaware
Zhi Tian
Zhi Tian George Mason University
Hao Huang
Hao Huang University of Pennsylvania
David G. Cahill
David G. Cahill University of Illinois at Urbana-Champaign
Hua Huang
Hua Huang University of California, Merced
Daniel C. Ralph
Daniel C. Ralph Cornell University

External Links

Personal website of Xin Fan

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Best Scientists Citing Xin Fan

Ken-ichi Uchida

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Eiji Saitoh

Eiji Saitoh

University of Tokyo

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Xiufeng Han

Xiufeng Han

Chinese Academy of Sciences

Publications: 36

Axel Hoffmann

Axel Hoffmann

University of Illinois at Urbana-Champaign

Publications: 34

Kang L. Wang

Kang L. Wang

University of California, Los Angeles

Publications: 33

Gerrit E. W. Bauer

Gerrit E. W. Bauer

Tohoku University

Publications: 32

Daniel C. Ralph

Daniel C. Ralph

Cornell University

Publications: 29

Rudolf Gross

Rudolf Gross

Technical University of Munich

Publications: 26

Junjun Jiang

Junjun Jiang

Harbin Institute of Technology

Publications: 26

Hao Huang

Hao Huang

University of Pennsylvania

Publications: 25

Kai Liu

Kai Liu

Georgetown University

Publications: 25

Robert A. Buhrman

Robert A. Buhrman

Cornell University

Publications: 22

John Q. Xiao

John Q. Xiao

University of Delaware

Publications: 22

Cheng Song

Cheng Song

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Feng Pan

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Manuel Vázquez

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