World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
20303
World Ranking
8138
National Ranking
1074

Naiyan 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 Naiyan 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: 75 publications — 2nd percentile

2% of scientists in this discipline score the same or lower.

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

Naiyan 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 Naiyan 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

Naiyan Wang is affiliated with the Hong Kong University of Science and Technology in China. Their research primarily spans the fields of Computer Science and Engineering, with a focus on specialized subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Automotive Engineering, and Computational Mechanics.

Their work covers a range of topics including Advanced Neural Network Applications, Video Surveillance and Tracking Methods, Advanced Image and Video Retrieval Techniques, Advanced Vision and Imaging, Robotics and Sensor-Based Localization, Autonomous Vehicle Technology and Safety, and Domain Adaptation and Few-Shot Learning.

Notable recent publications by Naiyan Wang include:

  • QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • RangeDet: In Defense of Range View for LiDAR-based 3D Object Detection, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Auto-Rectify Network for Unsupervised Indoor Depth Estimation, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • YOLOV: Making Still Image Object Detectors Great at Video Object Detection, 2023, Proceedings of the AAAI Conference on Artificial Intelligence
  • You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence

Frequent coauthors in Naiyan Wang's research include Zehao Huang, Zhaoxiang Zhang, Lue Fan, Yuntao Chen, and Zhichao Li, reflecting collaborative efforts across multiple studies.

The scholar's publications have appeared extensively in venues such as arXiv (Cornell University), IEEE Transactions on Pattern Analysis and Machine Intelligence, the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), the 2021 IEEE/CVF International Conference on Computer Vision (ICCV), and the International Journal of Computer Vision.

Best Publications

  • Empirical Evaluation of Rectified Activations in Convolutional Network.

    Bing Xu;Naiyan Wang;Tianqi Chen;Mu Li

  • MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

    Tianqi Chen;Mu Li;Yutian Li;Min Lin

  • The Visual Object Tracking VOT2016 Challenge Results

    Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg

  • Collaborative Deep Learning for Recommender Systems

    Hao Wang;Naiyan Wang;Dit-Yan Yeung

  • Learning a Deep Compact Image Representation for Visual Tracking

    Naiyan Wang;Dit-Yan Yeung

  • Scale-Aware Trident Networks for Object Detection

    Yanghao Li;Yuntao Chen;Naiyan Wang;Zhao-Xiang Zhang

  • Data-Driven Sparse Structure Selection for Deep Neural Networks

    Zehao Huang;Naiyan Wang

  • Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training

    Hongkai Zhang;Hong Chang;Bingpeng Ma;Naiyan Wang

  • Demystifying Neural Style Transfer

    Yanghao Li;Naiyan Wang;Jiaying Liu;Xiaodi Hou

  • Adaptive Batch Normalization for practical domain adaptation

    Yanghao Li;Naiyan Wang;Jianping Shi;Xiaodi Hou

  • QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection

    Unknown

  • Revisiting Batch Normalization For Practical Domain Adaptation

    Yanghao Li;Naiyan Wang;Jianping Shi;Jiaying Liu

  • Understanding and Diagnosing Visual Tracking Systems

    Naiyan Wang;Jianping Shi;Dit-Yan Yeung;Jiaya Jia

  • Like What You Like: Knowledge Distill via Neuron Selectivity Transfer.

    Zehao Huang;Naiyan Wang

  • Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

    Jia-Wang Bian;Zhichao Li;Naiyan Wang;Huangying Zhan

  • Transferring Rich Feature Hierarchies for Robust Visual Tracking

    Naiyan Wang;Siyi Li;Abhinav Gupta;Dit-Yan Yeung

  • DevNet: A Deep Event Network for multimedia event detection and evidence recounting

    Chuang Gan;Naiyan Wang;Yi Yang;Dit-Yan Yeung

  • Sequence Level Semantics Aggregation for Video Object Detection

    Haiping Wu;Yuntao Chen;Naiyan Wang;Zhao-Xiang Zhang

  • Cross View Fusion for 3D Human Pose Estimation

    Haibo Qiu;Chunyu Wang;Jingdong Wang;Naiyan Wang

  • RangeDet: In Defense of Range View for LiDAR-Based 3D Object Detection

    Lue Fan;Xuan Xiong;Feng Wang;Naiyan Wang

  • Online Robust Non-negative Dictionary Learning for Visual Tracking

    Naiyan Wang;Jingdong Wang;Dit-Yan Yeung

  • LiDAR R-CNN: An Efficient and Universal 3D Object Detector

    Zhichao Li;Feng Wang;Naiyan Wang

Frequent Co-Authors

Zhaoxiang Zhang
Zhaoxiang Zhang Chinese Academy of Sciences
Dit-Yan Yeung
Dit-Yan Yeung Hong Kong University of Science and Technology
Jiaying Liu
Jiaying Liu Peking University
Chunhua Shen
Chunhua Shen Zhejiang University
Jianping Shi
Jianping Shi SenseTime
Jingdong Wang
Jingdong Wang Baidu (China)
Ian Reid
Ian Reid University of Adelaide
Abhinav Gupta
Abhinav Gupta Carnegie Mellon University
Jiaya Jia
Jiaya Jia Hong Kong University of Science and Technology
Fatih Porikli
Fatih Porikli Australian National University

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