World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
11047
World Ranking
5583
National Ranking
335

Yi-Zhe Song 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 Yi-Zhe Song 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: 142 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Yi-Zhe Song 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 Yi-Zhe Song 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Yi-Zhe Song is affiliated with the University of Surrey in the United Kingdom and has an extensive publication record primarily in the field of computer science. The scientist's research concentrates on computer vision and pattern recognition, with significant contributions also in artificial intelligence, computational mechanics, computer graphics and computer-aided design, and control and systems engineering.

The research outputs include numerous papers published in reputed venues. Some recent notable papers are:

  • "The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification", 2020, IEEE Transactions on Image Processing
  • "Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer", 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Style-Based Global Appearance Flow for Virtual Try-On", 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Progressive Learning of Category-Consistent Multi-Granularity Features for Fine-Grained Visual Classification", 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Joint Visual Semantic Reasoning: Multi-Stage Decoder for Text Recognition", 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Yi-Zhe Song has collaborated frequently with several co-authors, including Tao Xiang, Aneeshan Sain, Pinaki Nath Chowdhury, Ayan Kumar Bhunia, and Zhanyu Ma. The collaboration count with these co-authors ranges from 26 to 87 joint publications.

The scientist's publication venues reflect active involvement in both conference and journal research communities. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Circuits and Systems for Video Technology
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The thematic focus of Yi-Zhe Song's work centers around several main topics, including:

  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Domain Adaptation and Few-Shot Learning
  • 3D Shape Modeling and Analysis
  • Human Pose and Action Recognition
  • Image Retrieval and Classification Techniques
  • Advanced Vision and Imaging

This profile highlights Yi-Zhe Song's role as a researcher with a diverse portfolio extending across multiple aspects of computer vision and machine learning, marked by a consistent output in both pioneering conferences and high-impact journals.

Best Publications

  • Learning to Generalize: Meta-Learning for Domain Generalization

    Da Li;Yongxin Yang;Yi-Zhe Song;Timothy M. Hospedales

  • Deeper, Broader and Artier Domain Generalization

    Da Li;Yongxin Yang;Yi-Zhe Song;Timothy M. Hospedales

  • Sketch Me That Shoe

    Qian Yu;Feng Liu;Yi-Zhe Song;Tao Xiang

  • Episodic Training for Domain Generalization

    Da Li;Jianshu Zhang;Yongxin Yang;Cong Liu

  • The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification

    Dongliang Chang;Yifeng Ding;Jiyang Xie;Ayan Kumar Bhunia

  • Fine-Grained Visual Classification via Progressive Multi-granularity Training of Jigsaw Patches

    Ruoyi Du;Dongliang Chang;Ayan Kumar Bhunia;Jiyang Xie

  • Sketch-a-Net: A Deep Neural Network that Beats Humans

    Qian Yu;Yongxin Yang;Feng Liu;Yi-Zhe Song

  • Fine-Grained Image Analysis with Deep Learning: A Survey

    Xiu-Shen Wei;Yi-Zhe Song;Oisin Mac Aodha;Jianxin Wu

  • Deep Spatial-Semantic Attention for Fine-Grained Sketch-Based Image Retrieval

    Jifei Song;Qian Yu;Yi-Zhe Song;Tao Xiang

  • Generalizable Person Re-Identification by Domain-Invariant Mapping Network

    Jifei Song;Yongxin Yang;Yi-Zhe Song;Tao Xiang

  • Sketch-based image retrieval via Siamese convolutional neural network

    Yonggang Qi;Yi-Zhe Song;Honggang Zhang;Jun Liu

  • Sketch-a-Net that Beats Humans

    Qian Yu;Yongxin Yang;Yi-Zhe Song;Tao Xiang

  • Simpler Is Better: Few-Shot Semantic Segmentation With Classifier Weight Transformer

    Zhihe Lu;Sen He;Xiatian Zhu;Li Zhang

  • Doodle to Search: Practical Zero-Shot Sketch-Based Image Retrieval

    Sounak Dey;Pau Riba;Anjan Dutta;Josep Llados Llados

  • Text extraction from natural scene image: A survey

    Honggang Zhang;Kaili Zhao;Yi-Zhe Song;Jun Guo

  • Stochastic Classifiers for Unsupervised Domain Adaptation

    Zhihe Lu;Yongxin Yang;Xiatian Zhu;Cong Liu

  • A survey on heterogeneous face recognition

    Shuxin Ouyang;Timothy Hospedales;Yi-Zhe Song;Xueming Li

  • SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval

    Peng Xu;Yongye Huang;Tongtong Yuan;Kaiyue Pang

  • Sketch Less for More: On-the-Fly Fine-Grained Sketch-Based Image Retrieval

    Ayan Kumar Bhunia;Yongxin Yang;Timothy M. Hospedales;Tao Xiang

  • Your “Flamingo” is My “Bird”: Fine-Grained, or Not

    Dongliang Chang;Kaiyue Pang;Yixiao Zheng;Zhanyu Ma

  • Variational Bayesian Learning for Dirichlet Process Mixture of Inverted Dirichlet Distributions in Non-Gaussian Image Feature Modeling

    Zhanyu Ma;Yuping Lai;W. Bastiaan Kleijn;Yi-Zhe Song

  • Free-hand sketch recognition by multi-kernel feature learning

    Yi Li;Timothy M. Hospedales;Yi-Zhe Song;Shaogang Gong

Frequent Co-Authors

Timothy M. Hospedales
Timothy M. Hospedales University of Edinburgh
Yongxin Yang
Yongxin Yang Queen Mary University of London
Zhanyu Ma
Zhanyu Ma Beijing University of Posts and Telecommunications
Honggang Zhang
Honggang Zhang Zhejiang University
Jun Guo
Jun Guo Beijing University of Posts and Telecommunications
Liang Wang
Liang Wang Chinese Academy of Sciences
Shaogang Gong
Shaogang Gong Queen Mary University of London
Bodo Rosenhahn
Bodo Rosenhahn University of Hannover
Xiatian Zhu
Xiatian Zhu University of Surrey
Christopher R. Bowen
Christopher R. Bowen University of Bath

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