World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
8932
World Ranking
5924
National Ranking
787

Zhiguo Cao 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 Zhiguo Cao 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: 201 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Zhiguo Cao 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 Zhiguo Cao 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: 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

Zhiguo Cao is affiliated with Huazhong University of Science and Technology in China. Their research primarily centers on the fields of Computer Science and Engineering, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Aerospace Engineering, and Computational Mechanics.

The scientist has produced a significant body of work, publishing extensively in topics that include Advanced Vision and Imaging, Video Surveillance and Tracking Methods, Advanced Image Processing Techniques, Advanced Image and Video Retrieval Techniques, Human Pose and Action Recognition, Image Processing Techniques and Applications, and Advanced Neural Network Applications.

Zhiguo Cao's research outputs appear in a variety of publication venues. Frequent venues include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Circuits and Systems for Video Technology

Some of the recent papers authored by Zhiguo Cao are:

  • An interpretable mortality prediction model for COVID-19 patients, 2020, Nature Machine Intelligence
  • A machine learning-based model for survival prediction in patients with severe COVID-19 infection, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • Interior Attention-Aware Network for Infrared Small Target Detection, 2022, IEEE Transactions on Geoscience and Remote Sensing
  • Decoupled Two-Stage Crowd Counting and Beyond, 2021, IEEE Transactions on Image Processing
  • Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Zhiguo Cao collaborates frequently with a number of researchers including Hao Lü, Ke Xian, Yang Xiao, Juewen Peng, and Zhiyu Pan. These collaborations have resulted in numerous joint publications.

Best Publications

  • An interpretable mortality prediction model for COVID-19 patients

    Li Yan;Hai Tao Zhang;Jorge Goncalves;Yang Xiao

  • A machine learning-based model for survival prediction in patients with severe COVID-19 infection

    Yan L;Zhang H;Goncalves J;Xiao Y

  • TasselNet: counting maize tassels in the wild via local counts regression network

    Hao Lu;Zhiguo Cao;Yang Xiao;Bohan Zhuang

  • VisDrone-DET2020: The Vision Meets Drone Object Detection in Image Challenge Results.

    Dawei Du;Longyin Wen;Pengfei Zhu;Heng Fan

  • A fast and robust local descriptor for 3D point cloud registration

    Jiaqi Yang;Zhiguo Cao;Qian Zhang

  • Monocular Relative Depth Perception with Web Stereo Data Supervision

    Ke Xian;Chunhua Shen;Zhiguo Cao;Hao Lu

  • From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer

    Haipeng Xiong;Hao Lu;Chengxin Liu;Liang Liu

  • A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation From a Single Depth Image

    Fu Xiong;Boshen Zhang;Yang Xiao;Zhiguo Cao

  • Structure-Guided Ranking Loss for Single Image Depth Prediction

    Ke Xian;Jianming Zhang;Oliver Wang;Long Mai

  • Automatic image-based detection technology for two critical growth stages of maize: Emergence and three-leaf stage

    Zhenghong Yu;Zhiguo Cao;Xi Wu;Xiaodong Bai

  • TOLDI: An effective and robust approach for 3D local shape description

    Jiaqi Yang;Qian Zhang;Yang Xiao;Zhiguo Cao

  • P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds

    Haozhe Qi;Chen Feng;Zhiguo Cao;Feng Zhao

  • Crop segmentation from images by morphology modeling in the CIE L*a*b* color space

    X. D. Bai;Z. G. Cao;Y. Wang;Z. H. Yu

  • TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks

    Haipeng Xiong;Zhiguo Cao;Hao Lu;Simon Madec

  • Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting

    Unknown

  • DeepCloud: Ground-Based Cloud Image Categorization Using Deep Convolutional Features

    Liang Ye;Zhiguo Cao;Yang Xiao

  • NM-Net: Mining Reliable Neighbors for Robust Feature Correspondences

    Chen Zhao;Zhiguo Cao;Chi Li;Xin Li

  • In-field automatic observation of wheat heading stage using computer vision

    Yanjun Zhu;Zhiguo Cao;Hao Lu;Yanan Li

  • Action Recognition for Depth Video using Multi-view Dynamic Images

    Yang Xiao;Jun Chen;Yancheng Wang;Zhiguo Cao

  • 3DV: 3D Dynamic Voxel for Action Recognition in Depth Video

    Yancheng Wang;Yang Xiao;Fu Xiong;Wenxiang Jiang

  • An Embarrassingly Simple Approach to Visual Domain Adaptation

    Hao Lu;Chunhua Shen;Zhiguo Cao;Yang Xiao

  • NTIRE 2019 Challenge on Real Image Denoising: Methods and Results

    Abdelrahman Abdelhamed;Radu Timofte;Michael S. Brown;Songhyun Yu

  • Deep Attention-Based Classification Network for Robust Depth Prediction

    Ruibo Li;Ke Xian;Chunhua Shen;Zhiguo Cao

Frequent Co-Authors

Chunhua Shen
Chunhua Shen Zhejiang University
Joey Tianyi Zhou
Joey Tianyi Zhou Agency for Science, Technology and Research
Junsong Yuan
Junsong Yuan University at Buffalo, State University of New York
Armin B. Cremers
Armin B. Cremers University of Bonn
Hai-Tao Zhang
Hai-Tao Zhang Huazhong University of Science and Technology
xin li
xin li Louisiana State University
Lei Zhu
Lei Zhu Tongji University
Luxin Yan
Luxin Yan Huazhong University of Science and Technology
Radu Timofte
Radu Timofte University of Wurzburg
Shugong Xu
Shugong Xu Shanghai University

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