World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
6374
World Ranking
12016
National Ranking
1486

Gang Zeng 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 Gang Zeng 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: 95 publications — 7th percentile

7% of scientists in this discipline score the same or lower.

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

Gang Zeng 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 Gang Zeng 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

Gang Zeng is affiliated with Peking University in China and specializes in research primarily within the fields of Computer Science and Engineering. Their work encompasses a range of subfields including Computer Vision and Pattern Recognition, Computational Mechanics, Computer Graphics and Computer-Aided Design, Aerospace Engineering, and Geology.

The scientist's research covers several main topics, with a particular focus on 3D Shape Modeling and Analysis, Computer Graphics and Visualization Techniques, Advanced Vision and Imaging, and Advanced Neural Network Applications. Additional areas of interest include Robotics and Sensor-Based Localization, 3D Surveying and Cultural Heritage, and Image Processing and 3D Reconstruction.

Gang Zeng has contributed to multiple recent publications, including:

  • Context Autoencoder for Self-supervised Representation Learning, 2023, International Journal of Computer Vision
  • Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision, 2021, arXiv (Cornell University)
  • Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation, 2020, arXiv (Cornell University)
  • MaskGroup: Hierarchical Point Grouping and Masking for 3D Instance Segmentation, 2022, 2022 IEEE International Conference on Multimedia and Expo (ICME)
  • Not All Voxels Are Equal: Semantic Scene Completion from the Point-Voxel Perspective, 2022, Proceedings of the AAAI Conference on Artificial Intelligence

Their collaborative efforts frequently involve coauthors such as Xiaokang Chen, Jingbo Wang, Jiaxiang Tang, and Ruijie Lu.

Gang Zeng's publications have appeared predominantly in venues like:

  • arXiv (Cornell University)
  • International Journal of Computer Vision
  • 2022 IEEE International Conference on Multimedia and Expo (ICME)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Best Publications

  • Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision

    Xiaokang Chen;Yuhui Yuan;Gang Zeng;Jingdong Wang

  • Image-based procedural modeling of facades

    Pascal Müller;Gang Zeng;Peter Wonka;Luc Van Gool

  • Context Autoencoder for Self-Supervised Representation Learning

    Unknown

  • Image-based plant modeling

    Long Quan;Ping Tan;Gang Zeng;Lu Yuan

  • Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation

    Xiaokang Chen;Kwan-Yee Lin;Jingbo Wang;Wayne Wu

  • Image-based tree modeling

    Ping Tan;Gang Zeng;Jingdong Wang;Sing Bing Kang

  • Image-based procedural modeling of facades

    Unknown

  • Complementary hashing for approximate nearest neighbor search

    Hao Xu;Jingdong Wang;Zhu Li;Gang Zeng

  • Scalable k-NN graph construction for visual descriptors

    Jing Wang;Jingdong Wang;Gang Zeng;Zhuowen Tu

  • Structure-Sensitive Superpixels via Geodesic Distance

    Peng Wang;Gang Zeng;Rui Gan;Jingdong Wang

  • Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignment

    Unknown

  • Image-based tree modeling

    Unknown

  • 3D Sketch-Aware Semantic Scene Completion via Semi-Supervised Structure Prior

    Xiaokang Chen;Kwan-Yee Lin;Chen Qian;Gang Zeng

  • Neural Style Transfer via Meta Networks

    Falong Shen;Shuicheng Yan;Gang Zeng

  • Fast approximate k-means via cluster closures

    Jing Wang;Jingdong Wang;Qifa Ke;Gang Zeng

  • Salient object detection for searched web images via global saliency

    Peng Wang;Jingdong Wang;Gang Zeng;Jie Feng

  • Optimizing kd-trees for scalable visual descriptor indexing

    You Jia;Jingdong Wang;Gang Zeng;Hongbin Zha

  • Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF

    Falong Shen;Rui Gan;Shuicheng Yan;Gang Zeng

  • Trinary-Projection Trees for Approximate Nearest Neighbor Search

    Jingdong Wang;Naiyan Wang;You Jia;Jian Li

  • Joint Implicit Image Function for Guided Depth Super-Resolution

    Jiaxiang Tang;Xiaokang Chen;Gang Zeng

  • Progressive surface reconstruction from images using a local prior

    Gang Zeng;S. Paris;L. Quan;F. Sillion

  • Similarity-Aware Patchwork Assembly for Depth Image Super-resolution

    Jing Li;Zhichao Lu;Gang Zeng;Rui Gan

  • Towards mass-produced building models

    Luc Van Gool;Gang Zeng;Filip Van den Borre;Pascal Müller

  • Supervised Kernel Descriptors for Visual Recognition

    Peng Wang;Jingdong Wang;Gang Zeng;Weiwei Xu

  • Structure-sensitive superpixels via geodesic distance

    Gang Zeng;Peng Wang;Jingdong Wang;Rui Gan

Frequent Co-Authors

Jingdong Wang
Jingdong Wang Baidu (China)
Hongbin Zha
Hongbin Zha Peking University
Long Quan
Long Quan Hong Kong University of Science and Technology
Shipeng Li
Shipeng Li Chinese University of Hong Kong, Shenzhen
Sylvain Paris
Sylvain Paris Adobe Systems (United States)
Long Wang
Long Wang Peking University
Peng Wang
Peng Wang Baidu (China)
Hongsheng Li
Hongsheng Li Chinese University of Hong Kong
Zhuowen Tu
Zhuowen Tu University of California, San Diego
François X. Sillion
François X. Sillion French Institute for Research in Computer Science and Automation - INRIA

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