World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
16841
World Ranking
3770
National Ranking
501

Yanwei 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 Yanwei 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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.

Yanwei 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 Yanwei Fu sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Overview

Yanwei Fu is affiliated with Fudan University in China and has contributed extensively to the field of computer science, with a primary focus on computer vision and related areas. Their body of work spans various subfields including computer vision and pattern recognition, artificial intelligence, computational mechanics, radiology, nuclear medicine and imaging, and computer graphics and computer-aided design.

Their research encompasses a range of topics, featuring prominently in areas such as:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Vision and Imaging
  • Human Pose and Action Recognition
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Computer Graphics and Visualization Techniques
  • 3D Shape Modeling and Analysis

Yanwei Fu has published in several notable venues, reflecting the breadth of their research output. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Image Processing

A selection of recent papers reflects the diversity of research topics and collaboration:

  • "Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers," 2020, arXiv (Cornell University)
  • "Learning a Few-shot Embedding Model with Contrastive Learning," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Pixel2Mesh: 3D Mesh Model Generation via Image Guided Deformation," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimation," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The scientist has worked collaboratively with several frequent co-authors, including:

  • Xiangyang Xue
  • Xuelin Qian
  • Chenjie Cao
  • Chengming Xu
  • Yu-Gang Jiang

Best Publications

  • Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

    Sixiao Zheng;Jiachen Lu;Hengshuang Zhao;Xiatian Zhu

  • Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

    Nanyang Wang;Yinda Zhang;Zhuwen Li;Yanwei Fu

  • Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

    Yang He;Yang He;Guoliang Kang;Xuanyi Dong;Yanwei Fu

  • Transductive Multi-View Zero-Shot Learning

    Yanwei Fu;Timothy M. Hospedales;Tao Xiang;Shaogang Gong

  • Pose-Normalized Image Generation for Person Re-identification

    Xuelin Qian;Yanwei Fu;Tao Xiang;Wenxuan Wang

  • Multi-Level Semantic Feature Augmentation for One-Shot Learning

    Zitian Chen;Yanwei Fu;Yinda Zhang;Yu-Gang Jiang

  • Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking

    Jinlong Peng;Changan Wang;Fangbin Wan;Yang Wu

  • Multi-scale Deep Learning Architectures for Person Re-identification

    Xuelin Qian;Yanwei Fu;Yu-Gang Jiang;Tao Xiang

  • Learning Salient Boundary Feature for Anchor-free Temporal Action Localization

    Chuming Lin;Chengming Xu;Donghao Luo;Yabiao Wang

  • Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation

    Yanwei Fu;Timothy M. Hospedales;Tao Xiang;Zhenyong Fu

  • Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation

    Chao Wen;Yinda Zhang;Zhuwen Li;Yanwei Fu

  • Image Deformation Meta-Networks for One-Shot Learning

    Zitian Chen;Yanwei Fu;Yu-Xiong Wang;Lin Ma

  • Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding

    Unknown

  • Multi-View Video Summarization

    Yanwei Fu;Yanwen Guo;Yanshu Zhu;Feng Liu

  • Instance Credibility Inference for Few-Shot Learning

    Yikai Wang;Chengming Xu;Chen Liu;Li Zhang

  • Recent Advances in Zero-Shot Recognition: Toward Data-Efficient Understanding of Visual Content

    Yanwei Fu;Tao Xiang;Yu-Gang Jiang;Xiangyang Xue

  • Learning Multimodal Latent Attributes

    Yanwei Fu;Timothy M. Hospedales;Tao Xiang;Shaogang Gong

  • Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks

    Yang He;Xuanyi Dong;Guoliang Kang;Yanwei Fu

  • Learning a Few-shot Embedding Model with Contrastive Learning

    Chen Liu;Yanwei Fu;Chengming Xu;Siqian Yang

  • Deep learning for video classification and captioning

    Zuxuan Wu;Ting Yao;Yanwei Fu;Yu-Gang Jiang

  • Attribute learning for understanding unstructured social activity

    Yanwei Fu;Timothy M. Hospedales;Tao Xiang;Shaogang Gong

  • Semi-supervised Vocabulary-Informed Learning

    Yanwei Fu;Leonid Sigal

  • Recent Advances in Zero-shot Recognition

    Yanwei Fu;Tao Xiang;Yu-Gang Jiang;Xiangyang Xue

Frequent Co-Authors

Xiangyang Xue
Xiangyang Xue Fudan University
Yu-Gang Jiang
Yu-Gang Jiang Fudan University
Leonid Sigal
Leonid Sigal University of British Columbia
Shaogang Gong
Shaogang Gong Queen Mary University of London
Yinda Zhang
Yinda Zhang Google (United States)
Timothy M. Hospedales
Timothy M. Hospedales University of Edinburgh
Feiyue Huang
Feiyue Huang Tencent (China)
Yizhou Wang
Yizhou Wang Peking University
Wei Liu
Wei Liu Tencent (China)
Jianfeng Feng
Jianfeng Feng Fudan University

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