World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
7412
World Ranking
11959
National Ranking
4885

Vladimir G. Kim 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 Vladimir G. Kim 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: 132 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Vladimir G. Kim 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 Vladimir G. Kim 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: 34 D-Index — 16th percentile

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

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

Overview

Vladimir G. Kim is affiliated with Adobe Systems in the United States. Their research primarily spans the fields of Computer Science and Engineering, with a strong focus on subfields such as Computational Mechanics, Computer Vision and Pattern Recognition, and Computer Graphics and Computer-Aided Design.

The scientist's body of work covers a range of topics including 3D Shape Modeling and Analysis, Computer Graphics and Visualization Techniques, Advanced Numerical Analysis Techniques, Image Processing and 3D Reconstruction, Manufacturing Process and Optimization, Advanced Vision and Imaging, and Human Pose and Action Recognition.

Recent publications highlight their contributions to computer graphics and vision conferences and journals. Selected papers include:

  • "AutoMate," 2021, ACM Transactions on Graphics
  • "Neural subdivision," 2020, ACM Transactions on Graphics
  • "Neural jacobian fields," 2022, ACM Transactions on Graphics
  • "GLASS: Geometric Latent Augmentation for Shape Spaces," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Neural Convolutional Surfaces," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Vladimir G. Kim frequently collaborates with several coauthors, including Noam Aigerman, Siddhartha Chaudhuri, Matthew Fisher, Niloy J. Mitra, and Adriana Schulz.

The venues in which the scientist often publishes include:

  • arXiv (Cornell University)
  • ACM Transactions on Graphics
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Computer Graphics Forum
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Best Publications

  • A scalable active framework for region annotation in 3D shape collections

    Li Yi;Vladimir G. Kim;Duygu Ceylan;I-Chao Shen

  • A Papier-Mâché Approach to Learning 3D Surface Generation

    Thibault Groueix;Matthew Fisher;Vladimir G. Kim;Bryan C. Russell

  • A Papier-Mache Approach to Learning 3D Surface Generation

    Thibault Groueix;Matthew Fisher;Vladimir G. Kim;Bryan C. Russell

  • Shape-based recognition of 3D point clouds in urban environments

    Aleksey Golovinskiy;Vladimir G. Kim;Thomas Funkhouser

  • Blended intrinsic maps

    Vladimir G. Kim;Yaron Lipman;Thomas Funkhouser

  • AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation

    Thibault Groueix;Matthew Fisher;Vladimir G. Kim;Bryan C. Russell

  • Multi-content GAN for Few-Shot Font Style Transfer

    Samaneh Azadi;Matthew Fisher;Vladimir Kim;Zhaowen Wang

  • 3D-CODED: 3D Correspondences by Deep Deformation

    Thibault Groueix;Matthew Fisher;Vladimir G. Kim;Bryan C. Russell

  • Blended intrinsic maps

    Unknown

  • Learning part-based templates from large collections of 3D shapes

    Vladimir G. Kim;Wilmot Li;Niloy J. Mitra;Siddhartha Chaudhuri

  • Convolutional neural networks on surfaces via seamless toric covers

    Haggai Maron;Meirav Galun;Noam Aigerman;Miri Trope

  • Structure-aware shape processing

    Niloy J. Mitra;Michael Wand;Hao Zhang;Daniel Cohen-Or

  • Exploring collections of 3D models using fuzzy correspondences

    Vladimir G. Kim;Wilmot Li;Niloy J. Mitra;Stephen DiVerdi

  • Entropic metric alignment for correspondence problems

    Justin Solomon;Gabriel Peyré;Vladimir G. Kim;Suvrit Sra

  • Data-driven structural priors for shape completion

    Minhyuk Sung;Vladimir G. Kim;Roland Angst;Leonidas Guibas

  • Learning Local Shape Descriptors from Part Correspondences with Multiview Convolutional Networks

    Haibin Huang;Evangelos Kalogerakis;Siddhartha Chaudhuri;Duygu Ceylan

  • Data-driven shape analysis and processing

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

  • Shape2Pose: human-centric shape analysis

    Vladimir G. Kim;Siddhartha Chaudhuri;Leonidas Guibas;Thomas Funkhouser

  • Rank algorithms for picture processing

    Unknown

  • Learning elementary structures for 3D shape generation and matching

    Theo Deprelle;Thibault Groueix;Matthew Fisher;Vladimir G. Kim

  • Neural Cages for Detail-Preserving 3D Deformations

    Wang Yifan;Noam Aigerman;Vladimir G. Kim;Siddhartha Chaudhuri

  • Physics-driven pattern adjustment for direct 3D garment editing

    Aric Bartle;Alla Sheffer;Vladimir G. Kim;Danny M. Kaufman

  • Möbius Transformations For Global Intrinsic Symmetry Analysis

    Vladimir G. Kim;Yaron Lipman;Xiaobai Chen;Thomas Allen Funkhouser

  • AtlasNet: A Papier-M\^ach'e Approach to Learning 3D Surface Generation

    Thibault Groueix;Matthew Fisher;Vladimir G. Kim;Bryan C. Russell

  • Data-Driven Shape Analysis and Processing

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

Frequent Co-Authors

Matthew Fisher
Matthew Fisher Adobe Systems (United States)
Siddhartha Chaudhuri
Siddhartha Chaudhuri Adobe Systems (United States)
Bryan C. Russell
Bryan C. Russell Adobe Systems (United States)
Niloy J. Mitra
Niloy J. Mitra University College London
Leonidas J. Guibas
Leonidas J. Guibas Stanford University
Thomas Funkhouser
Thomas Funkhouser Google (United States)
Ersin Yumer
Ersin Yumer Adobe Systems (United States)
Eli Shechtman
Eli Shechtman Adobe Systems (United States)
Evangelos Kalogerakis
Evangelos Kalogerakis Technical University of Crete
Yaron Lipman
Yaron Lipman Facebook (United States)

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