World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
15176
World Ranking
2902
National Ranking
109

Ping Tan 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 Ping Tan 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: 162 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

Ping Tan 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 Ping Tan 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: 62 D-Index — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Overview

Ping Tan is affiliated with Simon Fraser University in Canada and has contributed extensively to the fields of computer science and engineering. Their research focus centers primarily on computer vision and pattern recognition, with significant work addressing advanced vision and imaging challenges, robotics and sensor-based localization, and 3D shape modeling and analysis.

The subfields of study that dominate their research portfolio include:

  • Computer Vision and Pattern Recognition
  • Aerospace Engineering
  • Computational Mechanics
  • Media Technology
  • Artificial Intelligence

Within the scope of their work, prominent topics covered are:

  • Advanced Vision and Imaging
  • Robotics and Sensor-Based Localization
  • 3D Shape Modeling and Analysis
  • Human Pose and Action Recognition
  • Advanced Image and Video Retrieval Techniques
  • Optical measurement and interference techniques
  • Computer Graphics and Visualization Techniques

Ping Tan has published numerous papers across well-regarded venues in the field. Notable recent publications include:

  • Neural Window Fully-connected CRFs for Monocular Depth Estimation (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution (2021), presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Learning Guided Convolutional Network for Depth Completion (2020), published in IEEE Transactions on Image Processing
  • Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image (2021), presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Multi-View Photometric Stereo: A Robust Solution and Benchmark Dataset for Spatially Varying Isotropic Materials (2020), published in IEEE Transactions on Image Processing

The venues where Ping Tan frequently publishes their work include:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Image Processing
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Robotics and Automation Letters

Throughout their career, Ping Tan has collaborated with multiple researchers. Frequent coauthors are:

  • Siyu Zhu
  • Weihao Yuan
  • Hongan Wang
  • Shuaicheng Liu
  • Zhaopeng Cui

Best Publications

  • DualGAN: Unsupervised Dual Learning for Image-to-Image Translation

    Zili Yi;Hao Zhang;Ping Tan;Minglun Gong

  • Sketch2Photo: internet image montage

    Tao Chen;Ming-Ming Cheng;Ping Tan;Ariel Shamir

  • Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching

    Xiaodong Gu;Zhiwen Fan;Siyu Zhu;Zuozhuo Dai

  • Image-based plant modeling

    Long Quan;Ping Tan;Gang Zeng;Lu Yuan

  • CoSLAM: Collaborative Visual SLAM in Dynamic Environments

    Danping Zou;Ping Tan

  • Bundled camera paths for video stabilization

    Shuaicheng Liu;Lu Yuan;Ping Tan;Jian Sun

  • Richardson-Lucy Deblurring for Scenes under a Projective Motion Path

    Yu-Wing Tai;Ping Tan;M. S. Brown

  • Image-based tree modeling

    Ping Tan;Gang Zeng;Jingdong Wang;Sing Bing Kang

  • CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

    Lizhe Liu;Xiaohao Chen;Siyu Zhu;Ping Tan

  • PanoContext: A Whole-Room 3D Context Model for Panoramic Scene Understanding

    Yinda Zhang;Shuran Song;Ping Tan;Jianxiong Xiao

  • Learning Guided Convolutional Network for Depth Completion

    Jie Tang;Fei-Peng Tian;Wei Feng;Jian Li

  • Batch DropBlock Network for Person Re-Identification and Beyond

    Zuozhuo Dai;Mingqiang Chen;Xiaodong Gu;Siyu Zhu

  • Semantic colorization with internet images

    Alex Yong-Sang Chia;Shaojie Zhuo;Raj Kumar Gupta;Yu-Wing Tai

  • A Benchmark Dataset and Evaluation for Non-Lambertian and Uncalibrated Photometric Stereo

    Boxin Shi;Zhe Wu;Zhipeng Mo;Dinglong Duan

  • SteadyFlow: Spatially Smooth Optical Flow for Video Stabilization

    Shuaicheng Liu;Lu Yuan;Ping Tan;Jian Sun

  • Image-based façade modeling

    Jianxiong Xiao;Tian Fang;Ping Tan;Peng Zhao

  • A Closed-Form Solution to Retinex with Nonlocal Texture Constraints

    Qi Zhao;Ping Tan;Qiang Dai;Li Shen

  • Single image tree modeling

    Ping Tan;Tian Fang;Jianxiong Xiao;Peng Zhao

  • Highlight removal by illumination-constrained inpainting

    PingTan;Lin;Long Quan;Heung-Yeung Shum

  • A Benchmark Dataset and Evaluation for Non-Lambertian and Uncalibrated Photometric Stereo

    Boxin Shi;Zhipeng Mo;Zhe Wu;Dinglong Duan

  • BA-Net: Dense Bundle Adjustment Network

    Chengzhou Tang;Ping Tan

Frequent Co-Authors

Long Quan
Long Quan Hong Kong University of Science and Technology
Stephen Lin
Stephen Lin Microsoft Research Asia (China)
Boxin Shi
Boxin Shi Peking University
Lu Yuan
Lu Yuan Microsoft (United States)
Hao Zhang
Hao Zhang Simon Fraser University
Jianxiong Xiao
Jianxiong Xiao AutoX, Inc.
Jingdong Wang
Jingdong Wang Baidu (China)
Oliver Wang
Oliver Wang Adobe Systems (United States)
Yasuyuki Matsushita
Yasuyuki Matsushita Microsoft Research Asia Tokyo
Yinda Zhang
Yinda Zhang Google (United States)

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