World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
10689
World Ranking
11432
National Ranking
1418

Guangcan Liu 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 Guangcan Liu 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: 126 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

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

Guangcan Liu 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 Guangcan Liu 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Guangcan Liu is affiliated with Southeast University in China. Their research focuses primarily on the fields of computer science and engineering, with a concentration in computer vision and pattern recognition, artificial intelligence, media technology, computational mechanics, and biomedical engineering.

The body of work from Guangcan Liu includes 56 publications in computer science and 23 in engineering. Their subfields of study emphasize computer vision and pattern recognition with 34 papers, followed by artificial intelligence with 17 publications, and contributions to media technology, computational mechanics, and biomedical engineering.

Main research topics covered by Guangcan Liu span a range of areas:

  • Sparse and Compressive Sensing Techniques
  • Human Pose and Action Recognition
  • Domain Adaptation and Few-Shot Learning
  • Face and Expression Recognition
  • Remote-Sensing Image Classification
  • Advanced Neural Network Applications
  • Gait Recognition and Analysis

Frequent co-authors who have collaborated extensively with Guangcan Liu include:

  • Yisheng Zhu
  • Qingshan Liu
  • Fan Lyu
  • Kaile Du
  • Yifan Zhou

Notable publication venues where Guangcan Liu's work has appeared frequently are:

  • arXiv (Cornell University)
  • IEEE Transactions on Image Processing
  • The Visual Computer
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Information Theory

Selected recent papers authored or co-authored by Guangcan Liu include:

  • "Twin-Incoherent Self-Expressive Locality-Adaptive Latent Dictionary Pair Learning for Classification," 2020, IEEE Transactions on Neural Networks and Learning Systems
  • "Multilevel Spatial-Temporal Excited Graph Network for Skeleton-Based Action Recognition," 2022, IEEE Transactions on Image Processing
  • "Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space," 2020, IEEE Transactions on Image Processing
  • "Self-Supervised Video Representation Learning Using Improved Instance-Wise Contrastive Learning and Deep Clustering," 2022, IEEE Transactions on Circuits and Systems for Video Technology
  • "Recovery of Future Data via Convolution Nuclear Norm Minimization," 2022, IEEE Transactions on Information Theory

Best Publications

  • Robust Recovery of Subspace Structures by Low-Rank Representation

    Guangcan Liu;Zhouchen Lin;Shuicheng Yan;Ju Sun

  • Robust Subspace Segmentation by Low-Rank Representation

    Guangcan Liu;Zhouchen Lin;Yong Yu

  • Latent Low-Rank Representation for subspace segmentation and feature extraction

    Guangcan Liu;Shuicheng Yan

  • Low-Rank Tensor Constrained Multiview Subspace Clustering

    Changqing Zhang;Huazhu Fu;Si Liu;Guangcan Liu

  • Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set

    Si Liu;Zheng Song;Guangcan Liu;Changsheng Xu

  • Multi-task low-rank affinity pursuit for image segmentation

    Bin Cheng;Guangcan Liu;Jingdong Wang;Zhongyang Huang

  • Saliency Detection by Multitask Sparsity Pursuit

    Congyan Lang;Guangcan Liu;Jian Yu;Shuicheng Yan

  • Practical low-rank matrix approximation under robust L 1 -norm

    Yinqiang Zheng;Guangcan Liu;Shigeki Sugimoto;Shuicheng Yan

  • Inductive Robust Principal Component Analysis

    Bing-Kun Bao;Guangcan Liu;Changsheng Xu;Shuicheng Yan

  • Spatio-temporal convolutional features with nested LSTM for facial expression recognition

    Zhenbo Yu;Guangcan Liu;Qingshan Liu;Jiankang Deng

  • Active subspace: Toward scalable low-rank learning

    Guangcan Liu;Shuicheng Yan

  • Blind Image Deblurring Using Spectral Properties of Convolution Operators

    Guangcan Liu;Shiyu Chang;Yi Ma

  • Implicit Block Diagonal Low-Rank Representation

    Xingyu Xie;Xianglin Guo;Guangcan Liu;Jun Wang

  • Blessing of Dimensionality: Recovering Mixture Data via Dictionary Pursuit

    Guangcan Liu;Qingshan Liu;Ping Li

  • Exact Subspace Segmentation and Outlier Detection by Low-Rank Representation

    Guangcan Liu;Huan Xu;Shuicheng Yan

  • Joint Label Prediction Based Semi-Supervised Adaptive Concept Factorization for Robust Data Representation

    Zhao Zhang;Yan Zhang;Guangcan Liu;Jinhui Tang

  • Deeper cascaded peak-piloted network for weak expression recognition

    Zhenbo Yu;Qinshan Liu;Guangcan Liu

  • Learning image compressed sensing with sub-pixel convolutional generative adversarial network

    Yubao Sun;Jiwei Chen;Qingshan Liu;Guangcan Liu

  • Multilevel Spatial–Temporal Excited Graph Network for Skeleton-Based Action Recognition

    Unknown

  • Low-Rank Matrix Completion in the Presence of High Coherence

    Guangcan Liu;Ping Li

  • A Deterministic Analysis for LRR

    Guangcan Liu;Huan Xu;Jinhui Tang;Qingshan Liu

  • Differentiable Linearized ADMM.

    Xingyu Xie;Jianlong Wu;Guangcan Liu;Zhisheng Zhong

Frequent Co-Authors

Shuicheng Yan
Shuicheng Yan National University of Singapore
Zhao Zhang
Zhao Zhang Hefei University of Technology
Qingshan Liu
Qingshan Liu Nanjing University of Information Science and Technology
Sheng Li
Sheng Li University of Virginia
Zhouchen Lin
Zhouchen Lin Peking University
Yong Yu
Yong Yu Shanghai Jiao Tong University
Meng Wang
Meng Wang Hefei University of Technology
Shengyong Chen
Shengyong Chen Tianjin University of Technology
Ping Li
Ping Li Baidu (China)
Yi Ma
Yi Ma University of Hong Kong

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