World's Best Scientists 2026 revealed!
Chunhua Shen

Chunhua Shen

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Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
128
Citations
73853
World Ranking
104
National Ranking
12

Chunhua Shen 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 Chunhua Shen 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: 521 publications — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Chunhua Shen 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 Chunhua Shen 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: 128 D-Index — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Computer Science in China Leader Award
  • 2025 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in China Leader Award

Overview

Chunhua Shen is a researcher affiliated with Zhejiang University in China, primarily working in the field of Computer Science. Their work focuses strongly on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Radiology, Nuclear Medicine and Imaging, and Computational Mechanics.

Their main research topics include:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Image and Video Retrieval Techniques
  • Advanced Vision and Imaging
  • Multimodal Machine Learning Applications
  • Video Surveillance and Tracking Methods
  • Handwritten Text Recognition Techniques

Chunhua Shen's publication record spans multiple venues, with a significant number of contributions to:

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

Notable recent papers include:

  • "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation", 2021, International Journal of Computer Vision
  • "FCOS: A Simple and Strong Anchor-free Object Detector", 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Twins: Revisiting the Design of Spatial Attention in Vision Transformers", 2021, arXiv (Cornell University)
  • "SOLOv2: Dynamic and Fast Instance Segmentation", 2020, arXiv (Cornell University)
  • "Conditional Positional Encodings for Vision Transformers", 2021, arXiv (Cornell University)

Frequent collaborators in their research include the following co-authors:

  • Zhi Tian
  • Xinlong Wang
  • Wei Yin
  • Hao Chen
  • Anton van den Hengel

Best Publications

  • FCOS: Fully Convolutional One-Stage Object Detection

    Zhi Tian;Chunhua Shen;Hao Chen;Tong He

  • Deep Learning for Anomaly Detection: A Review

    Guansong Pang;Chunhua Shen;Longbing Cao;Anton Van Den Hengel

  • RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation

    Guosheng Lin;Anton Milan;Chunhua Shen;Ian Reid

  • Wider or Deeper: Revisiting the ResNet Model for Visual Recognition

    Zifeng Wu;Chunhua Shen;Anton van den Hengel

  • BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation

    Changqian Yu;Changqian Yu;Changxin Gao;Jingbo Wang;Gang Yu

  • Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections

    Xiao-Jiao Mao;Chunhua Shen;Yu-Bin Yang

  • Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

    Fayao Liu;Chunhua Shen;Guosheng Lin;Ian Reid

  • Supervised Discrete Hashing

    Fumin Shen;Chunhua Shen;Wei Liu;Heng Tao Shen

  • Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation

    Guosheng Lin;Chunhua Shen;Anton van den Hengel;Ian Reid

  • Deep convolutional neural fields for depth estimation from a single image

    Fayao Liu;Chunhua Shen;Guosheng Lin

  • A survey of appearance models in visual object tracking

    Xi Li;Weiming Hu;Chunhua Shen;Zhongfei Zhang

  • DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover’s Distance and Structured Classifiers

    Chi Zhang;Yujun Cai;Guosheng Lin;Chunhua Shen

  • FCOS: A Simple and Strong Anchor-free Object Detector.

    Zhi Tian;Chunhua Shen;Hao Chen;Tong He

  • SOLO: Segmenting Objects by Locations

    Xinlong Wang;Tao Kong;Chunhua Shen;Yuning Jiang

  • Conditional Convolutions for Instance Segmentation

    Zhi Tian;Chunhua Shen;Hao Chen

  • End-to-End Video Instance Segmentation with Transformers

    Yuqing Wang;Zhaoliang Xu;Xinlong Wang;Chunhua Shen

  • CANet: Class-Agnostic Segmentation Networks With Iterative Refinement and Attentive Few-Shot Learning

    Chi Zhang;Guosheng Lin;Fayao Liu;Rui Yao

  • Twins: Revisiting the Design of Spatial Attention in Vision Transformers

    Xiangxiang Chu;Zhi Tian;Yuqing Wang;Bo Zhang

  • Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs

    Bo Li;Chunhua Shen;Yuchao Dai;Anton van den Hengel

  • PolarMask: Single Shot Instance Segmentation With Polar Representation

    Enze Xie;Peize Sun;Xiaoge Song;Wenhai Wang

  • What Value Do Explicit High Level Concepts Have in Vision to Language Problems

    Qi Wu;Chunhua Shen;Lingqiao Liu;Anthony Dick

  • VITAL: VIsual Tracking via Adversarial Learning

    Yibing Song;Chao Ma;Xiaohe Wu;Lijun Gong

Frequent Co-Authors

Anton van den Hengel
Anton van den Hengel University of Adelaide
Lingqiao Liu
Lingqiao Liu University of Adelaide
Ian Reid
Ian Reid University of Adelaide
Guosheng Lin
Guosheng Lin Nanyang Technological University
Qi Wu
Qi Wu University of Adelaide
Qinfeng Shi
Qinfeng Shi University of Adelaide
Anthony Dick
Anthony Dick University of Adelaide
Jian Zhang
Jian Zhang University of Technology Sydney
Heng Tao Shen
Heng Tao Shen University of Electronic Science and Technology of China
Mingkui Tan
Mingkui Tan South China University of Technology

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