World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
11512
World Ranking
6383
National Ranking
381

Taku Komura 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 Taku Komura 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: 224 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Taku Komura 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 Taku Komura 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Taku Komura is affiliated with the University of Edinburgh in the United Kingdom and has contributed extensively to research in computer science and engineering. Their body of work spans various subfields, with a particular focus on computer vision and pattern recognition, computational mechanics, control and systems engineering, computer graphics and computer-aided design, and artificial intelligence.

Their research has been published in diverse venues, with frequent contributions to arXiv (Cornell University), ACM Transactions on Graphics, Computer Graphics Forum, Proceedings of the ACM on Computer Graphics and Interactive Techniques, and IEEE Transactions on Visualization and Computer Graphics.

Key recent publications include:

  • NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction (2021, arXiv (Cornell University))
  • FaceFormer: Speech-Driven 3D Facial Animation with Transformers (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR))
  • Local motion phases for learning multi-contact character movements (2020, ACM Transactions on Graphics)
  • DeepPhase (2022, ACM Transactions on Graphics)
  • MotioNet (2020, ACM Transactions on Graphics)

Their main research topics cover computer graphics and visualization techniques, human pose and action recognition, 3D shape modeling and analysis, human motion and animation, advanced vision and imaging, video analysis and summarization, as well as advanced numerical analysis techniques.

Taku Komura has collaborated frequently with several coauthors, including Wenping Wang, Lingjie Liu, Zhiyang Dou, Xiaoxiao Long, and Shiqing Xin.

Best Publications

  • Topology matching for fully automatic similarity estimation of 3D shapes

    Masaki Hilaga;Yoshihisa Shinagawa;Taku Kohmura;Tosiyasu L. Kunii

  • A deep learning framework for character motion synthesis and editing

    Daniel Holden;Jun Saito;Taku Komura

  • NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

    Peng Wang;Lingjie Liu;Yuan Liu;Christian Theobalt

  • Phase-functioned neural networks for character control

    Daniel Holden;Taku Komura;Jun Saito

  • A Virtual Reality Dance Training System Using Motion Capture Technology

    J C P Chan;H Leung;J K T Tang;T Komura

  • Learning motion manifolds with convolutional autoencoders

    Daniel Holden;Jun Saito;Taku Komura;Thomas Joyce

  • FaceFormer: Speech-Driven 3D Facial Animation with Transformers

    Unknown

  • Neural state machine for character-scene interactions

    Sebastian Starke;He Zhang;Taku Komura;Jun Saito

  • Mode-adaptive neural networks for quadruped motion control

    He Zhang;Sebastian Starke;Taku Komura;Jun Saito

  • Spatial relationship preserving character motion adaptation

    Edmond S. L. Ho;Taku Komura;Chiew-Lan Tai

  • A Recurrent Variational Autoencoder for Human Motion Synthesis

    Ikhsanul Habibie;Daniel Holden;Jonathan Schwarz;Joe Yearsley

  • Local motion phases for learning multi-contact character movements

    Sebastian Starke;Yiwei Zhao;Taku Komura;Kazi Zaman

  • DeepPhase

    Unknown

  • F2-NeRF: Fast Neural Radiance Field Training with Free Camera Trajectories

    Unknown

  • A Feedback Controller for Biped Humanoids that Can Counteract Large Perturbations During Gait

    T. Komura;H. Leung;Shunsuke Kudoh;J. Kuffner

  • Creating and retargetting motion by the musculoskeletal human body model

    Taku Komura;Yoshihisa Shinagawa;Tosiyasu L. Kunii

  • Computing inverse kinematics with linear programming

    Edmond S. L. Ho;Taku Komura;Rynson W. H. Lau

  • Simulating pathological gait using the enhanced linear inverted pendulum model

    T. Komura;A. Nagano;H. Leung;Y. Shinagawa

  • Optimal coordination of maximal-effort horizontal and vertical jump motions--a computer simulation study.

    Akinori Nagano;Taku Komura;Senshi Fukashiro

  • Interaction patches for multi-character animation

    Hubert P. H. Shum;Taku Komura;Masashi Shiraishi;Shuntaro Yamazaki

  • Relationship descriptors for interactive motion adaptation

    Rami Ali Al-Asqhar;Taku Komura;Myung Geol Choi

  • MotioNet: 3D Human Motion Reconstruction from Monocular Video with Skeleton Consistency

    Mingyi Shi;Kfir Aberman;Andreas Aristidou;Taku Komura

  • Character Motion Synthesis by Topology Coordinates

    Edmond S. L. Ho;Taku Komura

  • Proceedings of the Graphics Interface 2001 Conference

    Taku Komura;Yoshihisa Shinagawa

Frequent Co-Authors

Edmond S. L. Ho
Edmond S. L. Ho University of Glasgow
Rynson W. H. Lau
Rynson W. H. Lau City University of Hong Kong
Sethu Vijayakumar
Sethu Vijayakumar University of Edinburgh
Katsushi Ikeuchi
Katsushi Ikeuchi Microsoft (United States)
Kevin Duh
Kevin Duh Johns Hopkins University
Yuji Matsumoto
Yuji Matsumoto Nara Institute of Science and Technology
Tosiyasu L. Kunii
Tosiyasu L. Kunii University of Tokyo
Wenping Wang
Wenping Wang Texas A&M University
Joanna M. Wardlaw
Joanna M. Wardlaw University of Edinburgh
Daniel Cohen-Or
Daniel Cohen-Or Tel Aviv 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 exciting doors for those interested in computer science and related fields. Prospective students can begin their journey with an associate's degree online, which offers foundational skills and a flexible pathway into IT careers or further study.

For many, finding the right program also means considering budget and admission requirements. There are many cheap online colleges available, allowing students to minimize debt while gaining a quality education. Additionally, online schools that accept low gpa provide opportunities for students from all backgrounds to pursue their academic goals, even if they faced challenges in earlier studies.

Beyond core computer science, students can branch into fields like sustainability or technology applications in the environment. Curious about diverse pathways? Explore what can you do with an environmental science degree for more ideas on building a tech-driven, impactful career.

Best Scientists Citing Taku Komura

Trending Scientists

Recently Published Articles