World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
8625
World Ranking
6513
National Ranking
871

Hongbo Fu 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 Hongbo Fu 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: 206 publications — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Hongbo Fu 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 Hongbo Fu 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

Hongbo Fu is a researcher affiliated with the City University of Hong Kong in China. Their work spans multiple aspects of computer science and engineering, with a focus on computer vision, graphics, and pattern recognition. The breadth of their research covers several key subfields, including computer vision and pattern recognition, computational mechanics, computer graphics and computer-aided design, control and systems engineering, and geology.

The scientist's main areas of study involve 3D shape modeling and analysis, advanced vision and imaging, generative adversarial networks and image synthesis, computer graphics and visualization techniques, face recognition and analysis, human pose and action recognition, and human motion and animation.

Hongbo Fu has contributed extensively to the academic literature, publishing numerous papers in well-regarded venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Transactions on Visualization and Computer Graphics
  • ACM Transactions on Graphics
  • Computer Graphics Forum
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Some recent publications highlight a range of topics within their expertise:

  • DeepFaceDrawing, 2020, ACM Transactions on Graphics
  • SketchGNN: Semantic Sketch Segmentation with Graph Neural Networks, 2021, ACM Transactions on Graphics
  • Motif-GCNs With Local and Non-Local Temporal Blocks for Skeleton-Based Action Recognition, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • GCN-Denoiser: Mesh Denoising with Graph Convolutional Networks, 2022, ACM Transactions on Graphics
  • Supervoxel Convolution for Online 3D Semantic Segmentation, 2021, ACM Transactions on Graphics

Hongbo Fu often collaborates with several frequent co-authors, including Lin Gao, Shuyu Chen, Youyi Zheng, Yu-Kun Lai, and Chiew-Lan Tai.

Best Publications

  • TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers

    Unknown

  • D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features

    Xuyang Bai;Zixin Luo;Lei Zhou;Hongbo Fu

  • PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency

    Xuyang Bai;Zixin Luo;Lei Zhou;Hongkai Chen

  • Bilateral Normal Filtering for Mesh Denoising

    Youyi Zheng;Hongbo Fu;Oscar Kin-Chung Au;Chiew-Lan Tai

  • SDM-NET: deep generative network for structured deformable mesh

    Lin Gao;Jie Yang;Tong Wu;Yu-Jie Yuan

  • Parametric reshaping of human bodies in images

    Shizhe Zhou;Hongbo Fu;Ligang Liu;Daniel Cohen-Or

  • Sketch2Scene: sketch-based co-retrieval and co-placement of 3D models

    Kun Xu;Kang Chen;Hongbo Fu;Wei-Lun Sun

  • Upright orientation of man-made objects

    Hongbo Fu;Daniel Cohen-Or;Gideon Dror;Alla Sheffer

  • Structure recovery by part assembly

    Chao-Hui Shen;Hongbo Fu;Kang Chen;Shi-Min Hu

  • A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries

    Bo Li;Yijuan Lu;Chunyuan Li;Afzal Godil

  • Motion-aware temporal coherence for video resizing

    Yu-Shuen Wang;Hongbo Fu;Olga Sorkine;Tong-Yee Lee

  • Graph CNNs with Motif and Variable Temporal Block for Skeleton-Based Action Recognition.

    Yu-Hui Wen;Lin Gao;Hongbo Fu;Fang-Lue Zhang

  • DeepFaceDrawing: deep generation of face images from sketches

    Shu-Yu Chen;Wanchao Su;Lin Gao;Shihong Xia

  • Dual Laplacian editing for meshes

    O.K.-C. Au;C.L. Tai;L. Liu;H. Fu

  • End-to-End Learning Local Multi-View Descriptors for 3D Point Clouds

    Lei Li;Siyu Zhu;Hongbo Fu;Ping Tan

  • Adaptive partitioning of urban facades

    Chao-Hui Shen;Shi-Sheng Huang;Hongbo Fu;Shi-Min Hu

  • Adaptive synthesis of indoor scenes via activity-associated object relation graphs

    Qiang Fu;Xiaowu Chen;Xiaotian Wang;Sijia Wen

  • Component‐wise Controllers for Structure‐Preserving Shape Manipulation

    Youyi Zheng;Hongbo Fu;Daniel Cohen-Or;Oscar Kin-Chung Au

  • Electors Voting for Fast Automatic Shape Correspondence

    Oscar Kin-Chung Au;Chiew-Lan Tai;Daniel Cohen-Or;Youyi Zheng

  • JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds

    Zeyu Hu;Mingmin Zhen;Xuyang Bai;Hongbo Fu

  • A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface From Airborne LiDAR Data

    Wei-Lwun Lu;K.P. Murphy;J.J. Little;A. Sheffer

Frequent Co-Authors

Chiew-Lan Tai
Chiew-Lan Tai Hong Kong University of Science and Technology
Lin Gao
Lin Gao Xidian University
Xin Yang
Xin Yang Sun Yat-sen University
Yu-Kun Lai
Yu-Kun Lai Cardiff University
Xiaoguang Han
Xiaoguang Han Chinese University of Hong Kong
Shi-Min Hu
Shi-Min Hu Tsinghua University
Kun Zhou
Kun Zhou Zhejiang University
Ligang Liu
Ligang Liu University of Science and Technology of China
Daniel Cohen-Or
Daniel Cohen-Or Tel Aviv University
Alla Sheffer
Alla Sheffer University of British Columbia

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