World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
10619
World Ranking
7096
National Ranking
224

Qinfeng Shi 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 Qinfeng Shi 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: 178 publications — 38th percentile

38% of scientists in this discipline score the same or lower.

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

Qinfeng Shi 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 Qinfeng Shi 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Qinfeng Shi is affiliated with the University of Adelaide in Australia and has produced a significant amount of research within the field of Computer Science, specializing in areas intersecting Computer Vision and Pattern Recognition, Artificial Intelligence, Materials Chemistry, Biomedical Engineering, and Civil and Structural Engineering.

The scientist's research contributions include a notable focus on topics such as Domain Adaptation and Few-Shot Learning, Advanced Image Processing Techniques, Multimodal Machine Learning Applications, Image Enhancement Techniques, Anomaly Detection Techniques and Applications, Human Pose and Action Recognition, and Image and Signal Denoising Methods.

Qinfeng Shi has contributed to numerous publications, with frequent appearances in several leading venues. These include:

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

Among recent research works are the following papers:

  • "MOT20: A benchmark for multi object tracking in crowded scenes" (2020), arXiv (Cornell University)
  • "Deep HDR Imaging via A Non-Local Network" (2020), IEEE Transactions on Image Processing
  • "A Survey on Deep Neural Network Pruning: Taxonomy, Comparison, Analysis, and Recommendations" (2024), IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Attention-Guided Deep Neural Network With Multi-Scale Feature Fusion for Liver Vessel Segmentation" (2020), IEEE Journal of Biomedical and Health Informatics
  • "Implicit Sample Extension for Unsupervised Person Re-Identification" (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The scientist has collaborated frequently with several co-authors, including Anton van den Hengel, Dong Gong, Qingsen Yan, Yanning Zhang, and Ehsan Abbasnejad. These collaborations have resulted in multiple joint publications contributing to the fields mentioned above.

Best Publications

  • Image-Based Recommendations on Styles and Substitutes

    Julian McAuley;Christopher Targett;Qinfeng Shi;Anton van den Hengel

  • Fast Supervised Hashing with Decision Trees for High-Dimensional Data

    Guosheng Lin;Chunhua Shen;Qinfeng Shi;Anton van den Hengel

  • From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur

    Dong Gong;Jie Yang;Lingqiao Liu;Yanning Zhang

  • Real-time visual tracking using compressive sensing

    Hanxi Li;Chunhua Shen;Qinfeng Shi

  • Joint Probabilistic Data Association Revisited

    Seyed Hamid Rezatofighi;Anton Milan;Zhen Zhang;Qinfeng Shi

  • Is face recognition really a Compressive Sensing problem

    Qinfeng Shi;Anders Eriksson;Anton van den Hengel;Chunhua Shen

  • Attention-Guided Network for Ghost-Free High Dynamic Range Imaging

    Qingsen Yan;Dong Gong;Qinfeng Shi;Anton van den Hengel

  • A Survey on Deep Neural Network Pruning: Taxonomy, Comparison, Analysis, and Recommendations

    Unknown

  • Hash Kernels for Structured Data

    Qinfeng Shi;James Petterson;Gideon Dror;John Langford

  • Inductive Hashing on Manifolds

    Fumin Shen;Chunhua Shen;Qinfeng Shi;Anton van den Hengel

  • Part-Based Visual Tracking with Online Latent Structural Learning

    Rui Yao;Qinfeng Shi;Chunhua Shen;Yanning Zhang

  • Deep HDR Imaging via A Non-Local Network

    Qingsen Yan;Lei Zhang;Yu Liu;Yu Zhu

  • Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal

    Jie Yang;Dong Gong;Lingqiao Liu;Qinfeng Shi

  • Hashing on Nonlinear Manifolds

    Fumin Shen;Chunhua Shen;Qinfeng Shi;Anton van den Hengel

  • Implicit Sample Extension for Unsupervised Person Re-Identification

    Unknown

  • Discriminative human action segmentation and recognition using semi-Markov model

    Qinfeng Shi;Li Wang;Li Cheng;A. Smola

  • Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering

    Ming Yin;Junbin Gao;Zhouchen Lin;Qinfeng Shi

  • Sensor enabled wearable RFID technology for mitigating the risk of falls near beds

    Roberto L. Shinmoto Torres;D. C. Ranasinghe;Qinfeng Shi;A. P. Sample

  • Human Action Segmentation and Recognition Using Discriminative Semi-Markov Models

    Qinfeng Shi;Li Cheng;Li Wang;Alex Smola

  • Active Learning by Feature Mixing

    Unknown

  • COVID-19 Chest CT Image Segmentation -- A Deep Convolutional Neural Network Solution

    Qingsen Yan;Bo Wang;Dong Gong;Chuan Luo

  • Efficient Dense Labelling of Human Activity Sequences from Wearables using Fully Convolutional Networks

    Rui Yao;Rui Yao;Guosheng Lin;Qinfeng Shi;Damith Chinthana Ranasinghe

  • Counterfactual Vision and Language Learning

    Ehsan Abbasnejad;Damien Teney;Amin Parvaneh;Javen Shi

Frequent Co-Authors

Anton van den Hengel
Anton van den Hengel University of Adelaide
Chunhua Shen
Chunhua Shen Zhejiang University
Yanning Zhang
Yanning Zhang Northwestern Polytechnical University
Ian Reid
Ian Reid University of Adelaide
Mingkui Tan
Mingkui Tan South China University of Technology
Lei Zhang
Lei Zhang Hong Kong Polytechnic University
Damith C. Ranasinghe
Damith C. Ranasinghe University of Adelaide
Qingsen Yan
Qingsen Yan Northwestern Polytechnical University
Anthony Dick
Anthony Dick University of Adelaide
Lingqiao Liu
Lingqiao Liu University of Adelaide

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