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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 51 5445 5291 731 726 151 6861

Kai Xu publications per year

The chart shows the history of publications by Kai Xu between 2006 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Kai Xu published across 20 years, from 2006 to 2025, averaging 19 papers a year. Output peaked at 68 publications in 2023. 101 of the 380 publications appeared in the last two years.

No. of publications
20 40 60
Bar chart. Horizontal axis: year, 2006 to 2025. Vertical axis: number of publications, 0 to 68. Peak 68 publications in 2023. 2006: 2 publications 2007: 1 publication 2008: 3 publications 2009: 6 publications 2010: 3 publications 2011: 4 publications 2012: 7 publications 2013: 10 publications 2014: 12 publications 2015: 10 publications 2016: 14 publications 2017: 7 publications 2018: 14 publications 2019: 20 publications 2020: 16 publications 2021: 19 publications 2022: 63 publications 2023: 68 publications 2024: 41 publications 2025: 60 publications
2006 2025

380 publications in total across all disciplines

View publications per year as a table
Kai Xu: publications per year, 2006 to 2025
Year Publications
2006 2
2007 1
2008 3
2009 6
2010 3
2011 4
2012 7
2013 10
2014 12
2015 10
2016 14
2017 7
2018 14
2019 20
2020 16
2021 19
2022 63
2023 68
2024 41
2025 60
Total 380
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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.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 142–151 publications, is where this scientist sits. 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
32–41 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.

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609 151
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
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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.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 50–51 D-Index, is where this scientist sits. 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
30–31 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.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543 51
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
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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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