World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
6861
World Ranking
5445
National Ranking
731

Kai Xu 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 Kai Xu 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: 151 publications — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Kai Xu 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 Kai Xu 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: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Overview

Kai Xu is affiliated with the National University of Defense Technology in China and has an extensive publication record spanning the fields of Engineering and Computer Science. Their work primarily focuses on several key areas including Computer Vision and Pattern Recognition, Computational Mechanics, Aerospace Engineering, Geology, and Artificial Intelligence.

The scientist's research topics cover a range of subjects related to 3D shape modeling and analysis, advanced vision and imaging techniques, 3D surveying and cultural heritage, robotics and sensor-based localization, computer graphics and visualization techniques, advanced neural network applications, and robot manipulation and learning.

Kai Xu has published frequently with several collaborative partners. Notable frequent coauthors include Renjiao Yi, Chenyang Zhu, Hui Huang, Jiazhao Zhang, and Ruizhen Hu. Their body of work appears prominently in venues such as arXiv (Cornell University), SSRN Electronic Journal, ACM Transactions on Graphics, the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), and the Proceedings of the AAAI Conference on Artificial Intelligence.

Recent selected papers exemplify the scope of their research contributions:

  • Geometric Transformer for Fast and Robust Point Cloud Registration, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • ROSEFusion: Random Optimization for Online Dense Reconstruction under Fast Camera Motion, 2021, arXiv (Cornell University)
  • Multicentre, randomized comparison of two-stent and provisional stenting techniques in patients with complex coronary bifurcation lesions: the DEFINITION II trial, 2020, European Heart Journal
  • Efficient One-Pass Multi-View Subspace Clustering with Consensus Anchors, 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • RayMVSNet++: Learning Ray-Based 1D Implicit Fields for Accurate Multi-View Stereo, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence

Best Publications

  • GRASS: generative recursive autoencoders for shape structures

    Jun Li;Kai Xu;Siddhartha Chaudhuri;Ersin Yumer

  • GRAINS: Generative Recursive Autoencoders for INdoor Scenes

    Manyi Li;Akshay Gadi Patil;Kai Xu;Siddhartha Chaudhuri

  • MLCVNet: Multi-Level Context VoteNet for 3D Object Detection

    Qian Xie;Yu-Kun Lai;Jing Wu;Zhoutao Wang

  • A novel quantum representation for log-polar images

    Yi Zhang;Kai Lu;Yinghui Gao;Kai Xu

  • Fit and diverse: set evolution for inspiring 3D shape galleries

    Kai Xu;Hao Zhang;Daniel Cohen-Or;Baoquan Chen

  • Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation

    Dengsheng Chen;Jun Li;Zheng Wang;Kai Xu

  • GeoTransformer: Fast and Robust Point Cloud Registration With Geometric Transformer

    Unknown

  • PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes

    Rundi Wu;Yixin Zhuang;Kai Xu;Hao Zhang

  • Style-content separation by anisotropic part scales

    Kai Xu;Honghua Li;Hao Zhang;Daniel Cohen-Or

  • Symmetry Hierarchy of Man‐Made Objects

    Yanzhen Wang;Yanzhen Wang;Kai Xu;Kai Xu;Jun Li;Hao Zhang

  • Im2Struct: Recovering 3D Shape Structure from a Single RGB Image

    Chengjie Niu;Jun Li;Kai Xu

  • Data-driven shape analysis and processing

    Kai Xu;Vladimir G. Kim;Qixing Huang;Niloy Mitra

  • Partial intrinsic reflectional symmetry of 3D shapes

    Kai Xu;Hao Zhang;Andrea Tagliasacchi;Ligang Liu

  • Photo-inspired model-driven 3D object modeling

    Kai Xu;Hanlin Zheng;Hao Zhang;Daniel Cohen-Or

  • An efficient and effective convolutional auto-encoder extreme learning machine network for 3d feature learning

    Yueqing Wang;Zhige Xie;Kai Xu;Yong Dou

  • Online 3D Bin Packing with Constrained Deep Reinforcement Learning.

    Hang Zhao;Qijin She;Chenyang Zhu;Yin Yang

  • Local feature point extraction for quantum images

    Yi Zhang;Kai Lu;Kai Xu;Yinghui Gao

  • ASRO-DIO: Active Subspace Random Optimization Based Depth Inertial Odometry

    Unknown

  • 3D shape segmentation and labeling via extreme learning machine

    Zhige Xie;Kai Xu;Ligang Liu;Yueshan Xiong

  • Spatiotemporal CNN for Video Object Segmentation

    Kai Xu;Longyin Wen;Guorong Li;Liefeng Bo

  • Co-hierarchical analysis of shape structures

    Oliver van Kaick;Kai Xu;Hao Zhang;Yanzhen Wang

  • Multi-robot collaborative dense scene reconstruction

    Siyan Dong;Kai Xu;Qiang Zhou;Andrea Tagliasacchi

  • GRASS: Generative Recursive Autoencoders for Shape Structures

    Jun Li;Kai Xu;Siddhartha Chaudhuri;Ersin Yumer

  • Shape2Motion: Joint Analysis of Motion Parts and Attributes From 3D Shapes

    Xiaogang Wang;Bin Zhou;Yahao Shi;Xiaowu Chen

  • Data-Driven Shape Analysis and Processing

    Kai Xu;Vladimir G. Kim;Qixing Huang;Evangelos Kalogerakis

Frequent Co-Authors

Hao Zhang
Hao Zhang Simon Fraser University
Hui Huang
Hui Huang Shenzhen University
Baoquan Chen
Baoquan Chen Peking University
Daniel Cohen-Or
Daniel Cohen-Or Tel Aviv University
Dinesh Manocha
Dinesh Manocha University of Maryland, College Park
Siddhartha Chaudhuri
Siddhartha Chaudhuri Adobe Systems (United States)
Ligang Liu
Ligang Liu University of Science and Technology of China
Ariel Shamir
Ariel Shamir Reichman University
Leonidas J. Guibas
Leonidas J. Guibas Stanford University
Qingming Huang
Qingming Huang University of Chinese Academy of Sciences

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