World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
77
Citations
23694
World Ranking
1271
National Ranking
674

Ruigang Yang 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 Ruigang Yang 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: 281 publications — 70th percentile

70% of scientists in this discipline score the same or lower.

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

Ruigang Yang 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 Ruigang Yang 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: 77 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Overview

Ruigang Yang is affiliated with the University of Kentucky in the United States. Their research spans several primary fields of study including Computer Science and Engineering, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Aerospace Engineering, Automotive Engineering, Artificial Intelligence, and Computational Mechanics.

The scientist's work covers multiple key topics including Advanced Neural Network Applications, Advanced Vision and Imaging, Robotics and Sensor-Based Localization, Autonomous Vehicle Technology and Safety, Human Pose and Action Recognition, 3D Shape Modeling and Analysis, and Video Surveillance and Tracking Methods.

Yang has published extensively, with a significant presence in prominent venues. The most frequent publication venues include arXiv (Cornell University), IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the AAAI Conference on Artificial Intelligence, IEEE Robotics and Automation Letters, and the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Among recent notable papers, the following stand out:

  • Salient Object Detection in the Deep Learning Era: An In-Depth Survey (2021) published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion (2020) published in Proceedings of the AAAI Conference on Artificial Intelligence
  • Augmented LiDAR Simulator for Autonomous Driving (2020) published in IEEE Robotics and Automation Letters
  • Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-Based Perception (2021) published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Transformation-Equivariant 3D Object Detection for Autonomous Driving (2023) published in Proceedings of the AAAI Conference on Artificial Intelligence

Frequent collaborators in their research include Junbo Yin, Yuexin Ma, Xinge Zhu, Dinesh Manocha, and Dingfu Zhou. These close co-authorship relationships indicate ongoing partnerships within the fields of computer vision and machine learning.

Best Publications

  • Detailed Real-Time Urban 3D Reconstruction from Video

    M. Pollefeys;D. Nistér;J. M. Frahm;A. Akbarzadeh

  • Spatial-Depth Super Resolution for Range Images

    Qingxiong Yang;Ruigang Yang;J. Davis;D. Nister

  • Stereo Matching with Color-Weighted Correlation, Hierarchical Belief Propagation, and Occlusion Handling

    Qingxiong Yang;Liang Wang;Ruigang Yang;H. Stewenius

  • GA-Net: Guided Aggregation Net for End-To-End Stereo Matching

    Feihu Zhang;Victor Prisacariu;Ruigang Yang;Philip H.S. Torr

  • Salient Object Detection in the Deep Learning Era: An In-depth Survey.

    Wenguan Wang;Qiuxia Lai;Huazhu Fu;Jianbing Shen

  • The ApolloScape Dataset for Autonomous Driving

    Xinyu Huang;Xinjing Cheng;Qichuan Geng;Binbin Cao

  • The ApolloScape Open Dataset for Autonomous Driving and Its Application

    Xinyu Huang;Peng Wang;Xinjing Cheng;Dingfu Zhou

  • Real-Time Consensus-Based Scene Reconstruction Using Commodity Graphics Hardware†

    Ruigang Yang;Greg Welch;Gary Bishop

  • Multi-projector displays using camera-based registration

    R. Raskar;M.S. Brown;Ruigang Yang;Wei-Chao Chen

  • Saliency-Aware Video Object Segmentation

    Wenguan Wang;Jianbing Shen;Ruigang Yang;Fatih Porikli

  • TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents

    Yuexin Ma;Xinge Zhu;Sibo Zhang;Ruigang Yang

  • Real-Time Visibility-Based Fusion of Depth Maps

    P. Merrell;A. Akbarzadeh;Liang Wang;P. Mordohai

  • IoU Loss for 2D/3D Object Detection

    Dingfu Zhou;Jin Fang;Xibin Song;Chenye Guan

  • Multi-projector displays using camera-based registration

    Unknown

  • Multi-resolution real-time stereo on commodity graphics hardware

    Ruigang Yang;M. Pollefeys

  • High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming

    Liang Wang;Miao Liao;Minglun Gong;Ruigang Yang

  • Fusion of time-of-flight depth and stereo for high accuracy depth maps

    Jiejie Zhu;Liang Wang;Ruigang Yang;J. Davis

  • Real-time Global Stereo Matching Using Hierarchical Belief Propagation.

    Qingxiong Yang;Liang Wang;Ruigang Yang;Shengnan Wang

  • Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network

    Xinjing Cheng;Peng Wang;Ruigang Yang

  • Camera-based calibration techniques for seamless multiprojector displays

    M. Brown;A. Majumder;R. Yang

  • Stereo Matching with Color-Weighted Correlation, Hierachical Belief Propagation and Occlusion Handling

    Qyngxiong Yang;Liang Wang;Ruigang Yang;H. Stewenius

Frequent Co-Authors

Greg Welch
Greg Welch University of Central Florida
Peng Wang
Peng Wang Baidu (China)
Dinesh Manocha
Dinesh Manocha University of Maryland, College Park
Minglun Gong
Minglun Gong University of Guelph
Henry Fuchs
Henry Fuchs University of North Carolina at Chapel Hill
Marc Pollefeys
Marc Pollefeys ETH Zurich
James Davis
James Davis University of California, Santa Cruz
Qingxiong Yang
Qingxiong Yang City University of Hong Kong
Andrei State
Andrei State University of North Carolina at Chapel Hill
Michael S. Brown
Michael S. Brown York University

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