World's Best Scientists 2026 revealed!
Yaowei Wang

Yaowei Wang

D-Index & Metrics

Computer Science

D-Index
42
Citations
7226
World Ranking
8413
National Ranking
1096

Yaowei Wang 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 Yaowei Wang 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: 122 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Yaowei Wang 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 Yaowei Wang 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Yaowei Wang is affiliated with Peking University in China and has an extensive record in the field of computer science, specifically focusing on computer vision and pattern recognition. Their research contributions span multiple interconnected subfields and main topics within artificial intelligence and multimedia technology.

The scientist's published work heavily addresses areas such as:

  • Video Surveillance and Tracking Methods
  • Domain Adaptation and Few-Shot Learning
  • Advanced Image and Video Retrieval Techniques
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Anomaly Detection Techniques and Applications
  • Human Pose and Action Recognition

Yaowei Wang's recent and notable papers include:

  • Conformer: Local Features Coupling Global Representations for Visual Recognition, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • VMamba: Visual State Space Model, 2024, arXiv (Cornell University)
  • DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition, 2023, IEEE Transactions on Multimedia
  • Boosting Crowd Counting via Multifaceted Attention, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey, 2023, Machine Intelligence Research

Collaboration is a significant part of Wang's research outputs, with frequent co-authors including:

  • Yonghong Tian (31 publications)
  • Xiao Wang (20 publications)
  • Mingkui Tan (14 publications)
  • Kui Jia (11 publications)
  • Zhiheng Ma (10 publications)

Frequent publication venues reflect the interdisciplinary and multimedia focus of the researcher's work, with a high volume of publications appearing in:

  • arXiv (Cornell University)
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Neural Networks and Learning Systems
  • Proceedings of the AAAI Conference on Artificial Intelligence

The scientist's research portfolio is firmly rooted in computer science, with 442 publications overall, demonstrating specialization across areas like computer vision, artificial intelligence, electrical and electronic engineering, media technology, and transportation.

Best Publications

  • Deep Relative Distance Learning: Tell the Difference between Similar Vehicles

    Hongye Liu;Yonghong Tian;Yaowei Wang;Lu Pang

  • Conformer: Local Features Coupling Global Representations for Visual Recognition

    Zhiliang Peng;Wei Huang;Shanzhi Gu;Lingxi Xie

  • Unsupervised Cross-Dataset Transfer Learning for Person Re-identification

    Peixi Peng;Tao Xiang;Yaowei Wang;Massimiliano Pontil

  • Deep Transfer Learning for Person Re-identification

    Mengyue Geng;Yaowei Wang;Tao Xiang;Yonghong Tian

  • Boosting Crowd Counting via Multifaceted Attention

    Unknown

  • Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark

    Xiao Wang;Xiujun Shu;Zhipeng Zhang;Bo Jiang

  • Sequential Deep Trajectory Descriptor for Action Recognition With Three-Stream CNN

    Yemin Shi;Yonghong Tian;Yaowei Wang;Tiejun Huang

  • Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey

    Unknown

  • Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning

    Limeng Qiao;Yemin Shi;Jia Li;Yonghong Tian

  • Self-Supervised Attentive Generative Adversarial Networks for Video Anomaly Detection

    Unknown

  • AAformer: Auto-Aligned Transformer for Person Re-Identification.

    Kuan Zhu;Haiyun Guo;Shiliang Zhang;Yaowei Wang

  • VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows

    Unknown

  • Exploiting Multi-grain Ranking Constraints for Precisely Searching Visually-similar Vehicles

    Ke Yan;Yonghong Tian;Yaowei Wang;Wei Zeng

  • Abnormal Event Detection Using Deep Contrastive Learning for Intelligent Video Surveillance System

    Chao Huang;Zhihao Wu;Jie Wen;Yong Xu

  • A Survey of Crowd Counting and Density Estimation based on Convolutional Neural Network

    Zizhu Fan;Hong Zhang;Zheng Zhang;Guangming Lu

  • Joint Semantic and Latent Attribute Modelling for Cross-Class Transfer Learning

    Peixi Peng;Yonghong Tian;Tao Xiang;Yaowei Wang

  • Fine-Grained Object Classification via Self-Supervised Pose Alignment

    Unknown

  • CNN vs. SIFT for Image Retrieval: Alternative or Complementary?

    Ke Yan;Yaowei Wang;Dawei Liang;Tiejun Huang

  • Deep Transfer Learning for Person Re-Identification

    Haoran Chen;Yaowei Wang;Yemin Shi;Ke Yan

  • Robust multiple cameras pedestrian detection with multi-view Bayesian network

    Peixi Peng;Yonghong Tian;Yaowei Wang;Jia Li

  • Automatic webcam-based human heart rate measurements using laplacian eigenmap

    Lan Wei;Yonghong Tian;Yaowei Wang;Touradj Ebrahimi

  • Learning Long-Term Dependencies for Action Recognition with a Biologically-Inspired Deep Network

    Yemin Shi;Yonghong Tian;Yaowei Wang;Wei Zeng

  • P-ODN: Prototype-based Open Deep Network for Open Set Recognition.

    Yu Shu;Yemin Shi;Yaowei Wang;Tiejun Huang

  • Self-Supervision-Augmented Deep Autoencoder for Unsupervised Visual Anomaly Detection.

    Chao Huang;Zehua Yang;Jie Wen;Yong Xu

  • Contrastive Neural Architecture Search with Neural Architecture Comparators

    Yaofo Chen;Yong Guo;Qi Chen;Minli Li

Frequent Co-Authors

Yonghong Tian
Yonghong Tian Peking University
Tiejun Huang
Tiejun Huang Peking University
Feng Wu
Feng Wu University of Science and Technology of China
Yang Ren
Yang Ren City University of Hong Kong
Mingkui Tan
Mingkui Tan South China University of Technology
Peter K. Liaw
Peter K. Liaw University of Tennessee at Knoxville
Wen Gao
Wen Gao Peking University
Bin Luo
Bin Luo Anhui University
Qixiang Ye
Qixiang Ye Chinese Academy of Sciences
Wei-Shi Zheng
Wei-Shi Zheng Sun Yat-sen University

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