World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
11958
World Ranking
5045
National Ranking
680

Yuchao Dai 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 Yuchao Dai 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: 177 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Yuchao Dai 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 Yuchao Dai 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: 52 D-Index — 65th percentile

65% of scientists in this discipline score the same or lower.

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

Overview

Yuchao Dai is affiliated with Northwestern Polytechnical University in China and has contributed extensively to the fields of computer science and engineering, with a focus on computer vision and pattern recognition. Their body of work spans multiple subfields, including media technology, aerospace engineering, artificial intelligence, and computational mechanics.

The primary topics addressed in their research include:

  • Advanced Vision and Imaging
  • Advanced Image Processing Techniques
  • Advanced Image and Video Retrieval Techniques
  • Robotics and Sensor-Based Localization
  • Visual Attention and Saliency Detection
  • Optical Measurement and Interference Techniques
  • Image Processing Techniques and Applications

Yuchao Dai has published extensively in various academic venues. The most frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Transactions on Circuits and Systems for Video Technology
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Image Processing

Several recent papers attributed to Yuchao Dai's research contributions are:

  • Hierarchical Neural Architecture Search for Deep Stereo Matching, 2020, arXiv (Cornell University)
  • Deep learning based point cloud registration: an overview, 2020, Virtual Reality & Intelligent Hardware
  • Complementary Patch for Weakly Supervised Semantic Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Uncertainty Inspired RGB-D Saliency Detection, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • RGB-D Saliency Detection via Cascaded Mutual Information Minimization, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Frequent collaborators in their research include:

  • Yiran Zhong
  • Mingyi He
  • Hongdong Li
  • Nick Barnes
  • Bin Fan

Their work integrates a range of advanced methods related to image and video processing, sensor-based localization, and saliency detection in computer vision. This multidisciplinary approach is reflected in both the scope of their research topics and the diversity of publication venues.

Best Publications

  • NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

    Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang

  • Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs

    Bo Li;Chunhua Shen;Yuchao Dai;Anton van den Hengel

  • Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring

    Hongguang Zhang;Yuchao Dai;Hongdong Li;Piotr Koniusz

  • Simultaneously Localize, Segment and Rank the Camouflaged Objects

    Yunqiu Lv;Jing Zhang;Yuchao Dai;Aixuan Li

  • IoU Loss for 2D/3D Object Detection

    Dingfu Zhou;Jin Fang;Xibin Song;Chenye Guan

  • UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders

    Jing Zhang;Deng-Ping Fan;Yuchao Dai;Saeed Anwar

  • A Simple Prior-Free Method for Non-rigid Structure-from-Motion Factorization

    Yuchao Dai;Hongdong Li;Mingyi He

  • CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching

    Zhelun Shen;Yuchao Dai;Zhibo Rao

  • Weakly-Supervised Salient Object Detection via Scribble Annotations

    Jing Zhang;Xin Yu;Aixuan Li;Peipei Song

  • Uncertainty-aware Joint Salient Object and Camouflaged Object Detection

    Aixuan Li;Jing Zhang;Yunqiu Lv;Bowen Liu

  • Bringing a Blurry Frame Alive at High Frame-Rate With an Event Camera

    Liyuan Pan;Cedric Scheerlinck;Xin Yu;Richard Hartley

  • Skeleton based action recognition using translation-scale invariant image mapping and multi-scale deep CNN

    Bo Li;Yuchao Dai;Xuelian Cheng;Huahui Chen

  • Hierarchical Neural Architecture Search for Deep Stereo Matching

    Xuelian Cheng;Yiran Zhong;Mehrtash Harandi;Yuchao Dai

  • Self-Supervised Learning for Stereo Matching with Self-Improving Ability

    Yiran Zhong;Yuchao Dai;Hongdong Li

  • ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving

    Xibin Song;Peng Wang;Dingfu Zhou;Rui Zhu

  • Efficient Global 2D-3D Matching for Camera Localization in a Large-Scale 3D Map

    Liu Liu;Hongdong Li;Yuchao Dai

  • Rotation Averaging

    Unknown

  • Complementary Patch for Weakly Supervised Semantic Segmentation

    Fei Zhang;Chaochen Gu;Chenyue Zhang;Yuchao Dai

  • Monocular depth estimation with hierarchical fusion of dilated CNNs and soft-weighted-sum inference

    Bo Li;Yuchao Dai;Mingyi He

  • Deep learning based point cloud registration: an overview

    Zhiyuan Zhang;Yuchao Dai;Jiadai Sun

  • Skeleton based action recognition using translation-scale invariant image mapping and multi-scale deep cnn

    Bo Li;Mingyi He;Xuelian Cheng;Yucheng Chen

  • Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective

    Jing Zhang;Tong Zhang;Yuchao Dai;Mehrtash Harandi

Frequent Co-Authors

Hongdong Li
Hongdong Li Australian National University
Nick Barnes
Nick Barnes Australian National University
Richard Hartley
Richard Hartley Australian National University
Ruigang Yang
Ruigang Yang University of Kentucky
Fatih Porikli
Fatih Porikli Australian National University
Anoop Cherian
Anoop Cherian Mitsubishi Electric (United States)
Stan Birchfield
Stan Birchfield Nvidia (United States)
Quan Pan
Quan Pan Northwestern Polytechnical University
Tom Drummond
Tom Drummond Monash University
Deng-Ping Fan
Deng-Ping Fan Nankai University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Online education has opened new opportunities for those interested in Computer Science in the USA. Flexible program formats allow you to tailor your studies and access quality education, regardless of your background or location.

For those starting their journey, pursuing an associate degree online can provide foundational skills and a stepping stone to a bachelor's program. Many students are also looking for affordable online courses that fit within their budget, ensuring a cost-effective path to a rewarding tech career.

If you're worried about prior academic performance, there are online colleges that accept low gpa, making higher education accessible to a wider range of students. For professionals seeking to advance or specialize, exploring the most in demand masters degrees can lead to fields with strong job prospects and salary growth.

Whether you’re just starting out or aiming to upskill, online study offers flexible options that match your needs and goals.

Best Scientists Citing Yuchao Dai

Trending Scientists

Recently Published Articles