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2025

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Rising Stars

D-Index
44
Citations
9364
World Ranking
481
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161

Computer Science

D-Index
45
Citations
10613
World Ranking
7098
National Ranking
943

Runmin Cong 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 Runmin Cong 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: 249 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: 559 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: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 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: 155 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Runmin Cong 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 Runmin Cong sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Runmin Cong is affiliated with Shandong University in China and has contributed extensively to the field of computer science, with a primary focus on computer vision and pattern recognition. Their research spans advanced techniques in image processing and artificial intelligence, with particular emphasis on visual attention and saliency detection.

The scientist's recent publications include:

  • Global Context-Aware Progressive Aggregation Network for Salient Object Detection, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Image Dehazing Transformer with Transmission-Aware 3D Position Embedding, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images, 2020, IEEE Transactions on Image Processing
  • ASIF-Net: Attention Steered Interweave Fusion Network for RGB-D Salient Object Detection, 2020, IEEE Transactions on Cybernetics
  • Underwater Image Enhancement Quality Evaluation: Benchmark Dataset and Objective Metric, 2022, IEEE Transactions on Circuits and Systems for Video Technology

The scientist frequently collaborates with other researchers, with the most common co-authors being:

  • Sam Kwong (55 collaborations)
  • Yao Zhao (49 collaborations)
  • Chongyi Li (21 collaborations)
  • Qingming Huang (17 collaborations)
  • Qiuping Jiang (17 collaborations)

Runmin Cong publishes mainly in venues known for computer vision and multimedia research. Frequent publication venues include:

  • arXiv (Cornell University) with 49 papers
  • IEEE Transactions on Image Processing with 12 papers
  • IEEE Transactions on Multimedia with 10 papers
  • IEEE Transactions on Circuits and Systems for Video Technology with 9 papers
  • IEEE Transactions on Geoscience and Remote Sensing with 5 papers

The primary fields of study for this scientist are squarely within computer science, with extensive work in subfields such as:

  • Computer Vision and Pattern Recognition (204 publications)
  • Media Technology (45 publications)
  • Artificial Intelligence (19 publications)
  • Radiology, Nuclear Medicine and Imaging (13 publications)
  • Cognitive Neuroscience (12 publications)

The main research topics covered by Runmin Cong's work include:

  • Visual Attention and Saliency Detection (96 publications)
  • Advanced Image Fusion Techniques (56 publications)
  • Advanced Image Processing Techniques (54 publications)
  • Advanced Neural Network Applications (52 publications)
  • Image Enhancement Techniques (42 publications)
  • Advanced Image and Video Retrieval Techniques (42 publications)
  • Advanced Vision and Imaging (28 publications)

Best Publications

  • Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement

    Chunle Guo;Chongyi Li;Jichang Guo;Chen Change Loy

  • An Underwater Image Enhancement Benchmark Dataset and Beyond

    Chongyi Li;Chunle Guo;Wenqi Ren;Runmin Cong

  • Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding

    Chongyi Li;Saeed Anwar;Junhui Hou;Runmin Cong

  • Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior

    Chong-Yi Li;Ji-Chang Guo;Run-Min Cong;Yan-Wei Pang

  • Image Dehazing Transformer with Transmission-Aware 3D Position Embedding

    Unknown

  • Global Context-Aware Progressive Aggregation Network for Salient Object Detection

    Zuyao Chen;Qianqian Xu;Runmin Cong;Qingming Huang

  • Review of Visual Saliency Detection With Comprehensive Information

    Runmin Cong;Jianjun Lei;Huazhu Fu;Ming-Ming Cheng

  • Nested Network With Two-Stream Pyramid for Salient Object Detection in Optical Remote Sensing Images

    Chongyi Li;Runmin Cong;Junhui Hou;Sanyi Zhang

  • Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images

    Qijian Zhang;Runmin Cong;Chongyi Li;Ming-Ming Cheng

  • Underwater Image Enhancement Quality Evaluation: Benchmark Dataset and Objective Metric

    Unknown

  • PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN With Dual-Discriminators

    Unknown

  • Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion

    Runmin Cong;Jianjun Lei;Changqing Zhang;Qingming Huang

  • ASIF-Net: Attention Steered Interweave Fusion Network for RGB-D Salient Object Detection

    Chongyi Li;Runmin Cong;Sam Kwong;Junhui Hou

  • A hybrid method for underwater image correction

    Chongyi Li;Jichang Guo;Chunle Guo;Runmin Cong

  • CIR-Net: Cross-Modality Interaction and Refinement for RGB-D Salient Object Detection

    Unknown

  • Hierarchical Features Driven Residual Learning for Depth Map Super-Resolution

    Chunle Guo;Chongyi Li;Jichang Guo;Runmin Cong

  • DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection

    Zuyao Chen;Runmin Cong;Qianqian Xu;Qingming Huang

  • WaveNet: Wavelet Network With Knowledge Distillation for RGB-T Salient Object Detection

    Unknown

  • RRNet: Relational Reasoning Network with Parallel Multi-scale Attention for Salient Object Detection in Optical Remote Sensing Images

    Runmin Cong;Yumo Zhang;Leyuan Fang;Jun Li

  • Unsupervised Decomposition and Correction Network for Low-Light Image Enhancement

    Unknown

  • RGB-D Salient Object Detection with Cross-Modality Modulation and Selection

    Chongyi Li;Runmin Cong;Yongri Piao;Qianqian Xu

  • Going From RGB to RGBD Saliency: A Depth-Guided Transformation Model

    Runmin Cong;Jianjun Lei;Huazhu Fu;Junhui Hou

  • PDR-Net: Perception-Inspired Single Image Dehazing Network With Refinement

    Chongyi Li;Chunle Guo;Jichang Guo;Ping Han

  • Co-Saliency Detection for RGBD Images Based on Multi-Constraint Feature Matching and Cross Label Propagation

    Runmin Cong;Jianjun Lei;Huazhu Fu;Qingming Huang

  • Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement

    Chunle Guo;Chongyi Li;Jichang Guo;Chen Change Loy

  • An Iterative Co-Saliency Framework for RGBD Images

    Runmin Cong;Jianjun Lei;Huazhu Fu;Weisi Lin

  • Perceptual hashing for image authentication: A survey

    Ling Du;Anthony T.S. Ho;Anthony T.S. Ho;Anthony T.S. Ho;Runmin Cong

Frequent Co-Authors

Sam Kwong
Sam Kwong Lingnan University
Huazhu Fu
Huazhu Fu Agency for Science, Technology and Research
Qingming Huang
Qingming Huang University of Chinese Academy of Sciences
Yao Zhao
Yao Zhao Beijing Jiaotong University
Junhui Hou
Junhui Hou City University of Hong Kong
Xiaochun Cao
Xiaochun Cao Sun Yat-sen University
Chunping Hou
Chunping Hou Tianjin University
Wenqi Ren
Wenqi Ren Sun Yat-sen University
Weisi Lin
Weisi Lin Nanyang Technological University
Ming-Ming Cheng
Ming-Ming Cheng Nankai University

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