World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
6009
World Ranking
11197
National Ranking
1373

Ying Shan 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 Ying Shan 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: 77 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Ying Shan 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 Ying Shan 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Ying Shan is affiliated with Tencent (China), based in China, and specializes primarily in computer science with a focus on computer vision and related subfields. Their research encompasses areas such as computer vision and pattern recognition, artificial intelligence, signal processing, computational mechanics, and computer graphics and computer-aided design.

Their main research topics include multimodal machine learning applications, generative adversarial networks and image synthesis, advanced vision and imaging, advanced image and video retrieval techniques, human pose and action recognition, video analysis and summarization, and advanced image processing techniques.

Ying Shan has multiple frequent collaborators including Yixiao Ge, Xintao Wang, Yan-Pei Cao, Zhongang Qi, and Xiaodong Cun. Their work has been published extensively, with many contributions to venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Circuits and Systems for Video Technology
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • SSRN Electronic Journal

Recent notable papers authored or co-authored by Ying Shan include:

  • T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models, 2024, Proceedings of the AAAI Conference on Artificial Intelligence
  • UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Bridging Video-text Retrieval with Multiple Choice Questions, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Crossover Learning for Fast Online Video Instance Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data, 2021, arXiv (Cornell University)

Best Publications

  • Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

    Xintao Wang;Liangbin Xie;Chao Dong;Ying Shan

  • Towards Real-World Blind Face Restoration with Generative Facial Prior

    Xintao Wang;Yu Li;Honglun Zhang;Ying Shan

  • Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features

    Ying Shan;T. Ryan Hoens;Jian Jiao;Haijing Wang

  • Expressive expression mapping with ratio images

    Zicheng Liu;Ying Shan;Zhengyou Zhang

  • Visual panel: virtual mouse, keyboard and 3D controller with an ordinary piece of paper

    Zhengyou Zhang;Ying Wu;Ying Shan;Steven Shafer

  • Model-based bundle adjustment with application to face modeling

    Ying Shan;Zicheng Liu;Zhengyou Zhang

  • System and method for providing a mobile input device

    Zhengyou Zhang;Ying Shan;Steven A. N. Shafer;Ying Wu

  • Robust and Rapid Generation of Animated Faces from Video Images: A Model-Based Modeling Approach

    Zhengyou Zhang;Zicheng Liu;Dennis Adler;Michael F. Cohen

  • Rapid object indexing using locality sensitive hashing and joint 3D-signature space estimation

    B. Matei;Ying Shan;H.S. Sawhney;Yi Tan

  • Fast Video Object Segmentation Using the Global Context Module

    Yu Li;Zhuoran Shen;Ying Shan

  • System and method for transforming an ordinary computer monitor into a touch screen

    Zhengyou Zhang;Ying Shan

  • Open-book Video Captioning with Retrieve-Copy-Generate Network

    Ziqi Zhang;Zhongang Qi;Chunfeng Yuan;Ying Shan

  • Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Nonoverlapping Cameras

    Ying Shan;H.S. Sawhney;R. Kumar

  • Incremental motion estimation through local bundle adjustment

    Zhengyou Zhang;Ying Shan

  • System and method for progressive stereo matching of digital images

    Zhengyou Zhang;Ying Shan

  • Cross-modal Consensus Network for Weakly Supervised Temporal Action Localization

    Fa-Ting Hong;Jia-Chang Feng;Dan Xu;Ying Shan

  • Crossover Learning for Fast Online Video Instance Segmentation

    Shusheng Yang;Yuxin Fang;Xinggang Wang;Yu Li

  • Sub-pixel location of edges with non-uniform blurring: a finite closed-form approach

    Y. Shan;G.W. Boon

  • System and method for detecting still objects in images

    Feng Han;Ying Shan;Ryan Cekander;Harpreet S. Sawhney

  • Method and apparatus for tracking a movable object

    Yanlin Guo;Harpreet Sawhney;Rakesh Kumar;Ying Shan

  • A Progressive Scheme for Stereo Matching

    Zhengyou Zhang;Ying Shan

  • Object modeling system and process employing noise elimination and robust surface extraction techniques

    Zhengyou Zhang;Charles Loop;Ying Shan

Frequent Co-Authors

Zhengyou Zhang
Zhengyou Zhang Tencent (China)
Harpreet Sawhney
Harpreet Sawhney Microsoft (United States)
Rakesh Kumar
Rakesh Kumar SRI International
Zicheng Liu
Zicheng Liu Microsoft (United States)
Jianchang Mao
Jianchang Mao Google (United States)
Xinggang Wang
Xinggang Wang Huazhong University of Science and Technology
Wenyu Liu
Wenyu Liu Huazhong University of Science and Technology
Dong Yu
Dong Yu Tencent (China)
Ying Wu
Ying Wu Northwestern University
Chao Dong
Chao Dong Shenzhen Institutes of Advanced Technology

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