World's Best Scientists 2026 revealed!

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 50 5489 5335 77 77 177 16169

Guosheng Lin publications per year

The chart shows the history of publications by Guosheng Lin between 2009 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Guosheng Lin published across 17 years, from 2009 to 2025, averaging 19.4 papers a year. Output peaked at 68 publications in 2024. 110 of the 330 publications appeared in the last two years.

No. of publications
20 40 60
Bar chart. Horizontal axis: year, 2009 to 2025. Vertical axis: number of publications, 0 to 68. Peak 68 publications in 2024. 2009: 1 publication 2010: 0 publications 2011: 0 publications 2012: 1 publication 2013: 3 publications 2014: 3 publications 2015: 6 publications 2016: 6 publications 2017: 8 publications 2018: 10 publications 2019: 14 publications 2020: 24 publications 2021: 50 publications 2022: 38 publications 2023: 56 publications 2024: 68 publications 2025: 42 publications
2009 2025

330 publications in total across all disciplines

View publications per year as a table
Guosheng Lin: publications per year, 2009 to 2025
Year Publications
2009 1
2010 0
2011 0
2012 1
2013 3
2014 3
2015 6
2016 6
2017 8
2018 10
2019 14
2020 24
2021 50
2022 38
2023 56
2024 68
2025 42
Total 330
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Guosheng Lin 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 Guosheng Lin sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 172–181 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 177 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556 177
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
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Guosheng Lin 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 Guosheng Lin sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 50–51 D-Index, is where this scientist sits. 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
30–31 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.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543 50
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
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Overview

Guosheng Lin is affiliated with Nanyang Technological University in Singapore and has a substantial body of research within the fields of Computer Science and Engineering. Their work predominantly focuses on Computer Vision and Pattern Recognition, alongside significant contributions to Artificial Intelligence, Computational Mechanics, Computer Graphics and Computer-Aided Design, and Geology.

Their research spans several main topics, including:

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

Guosheng Lin has authored numerous publications, frequently contributing to journals and conferences such as arXiv (Cornell University), IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, SSRN Electronic Journal, and IEEE Transactions on Multimedia.

Their recent notable papers include:

  • Video Object Segmentation and Tracking, 2020, ACM Transactions on Intelligent Systems and Technology
  • Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Learning Meta-class Memory for Few-Shot Semantic Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • A Unified Transformer Framework for Group-Based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detection, 2023, IEEE Transactions on Multimedia
  • DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence

Collaboration has been a significant aspect of Guosheng Lin's research, with frequent co-authors including Fayao Liu, Qingyao Wu, Zhiguo Cao, Weide Liu, and Zhonghua Wu. These partnerships have contributed to a diverse and robust research portfolio.

Best Publications

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

    Guosheng Lin;Anton Milan;Chunhua Shen;Ian Reid

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

    Fayao Liu;Chunhua Shen;Guosheng Lin;Ian Reid

  • 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

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

    Chi Zhang;Yujun Cai;Guosheng Lin;Chunhua Shen

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

    Chi Zhang;Guosheng Lin;Fayao Liu;Rui Yao

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

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

  • Pyramid Graph Networks With Connection Attentions for Region-Based One-Shot Semantic Segmentation

    Chi Zhang;Guosheng Lin;Fayao Liu;Jiushuang Guo

  • Few-Shot Incremental Learning with Continually Evolved Classifiers

    Chi Zhang;Nan Song;Guosheng Lin;Yun Zheng

  • CRNet: Cross-Reference Networks for Few-Shot Segmentation

    Weide Liu;Chi Zhang;Guosheng Lin;Fayao Liu

  • CRF learning with CNN features for image segmentation

    Fayao Liu;Guosheng Lin;Chunhua Shen

  • Video Object Segmentation and Tracking: A Survey

    Rui Yao;Guosheng Lin;Shixiong Xia;Jiaqi Zhao

  • A General Two-Step Approach to Learning-Based Hashing

    Guosheng Lin;Chunhua Shen;David Suter;Anton Van Den Hengel

  • Progressive Modality Reinforcement for Human Multimodal Emotion Recognition from Unaligned Multimodal Sequences

    Fengmao Lv;Xiang Chen;Yanyong Huang;Lixin Duan

  • Exploring Context with Deep Structured Models for Semantic Segmentation

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

  • A Dilated Inception Network for Visual Saliency Prediction

    Sheng Yang;Guosheng Lin;Qiuping Jiang;Weisi Lin

  • MoNet: Deep Motion Exploitation for Video Object Segmentation

    Huaxin Xiao;Jiashi Feng;Guosheng Lin;Yu Liu

  • Multi-Path Region Mining for Weakly Supervised 3D Semantic Segmentation on Point Clouds

    Jiacheng Wei;Guosheng Lin;Kim-Hui Yap;Tzu-Yi Hung

  • Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation

    Yukun Su;Ruizhou Sun;Guosheng Lin;Qingyao Wu

  • Learning Hash Functions Using Column Generation

    Xi Li;Guosheng Lin;Chunhua Shen;Anton Van den Hengel

  • RefineNet: Multi-Path Refinement Networks for Dense Prediction

    Guosheng Lin;Fayao Liu;Anton Milan;Chunhua Shen

  • Fast Training of Triplet-Based Deep Binary Embedding Networks

    Bohan Zhuang;Guosheng Lin;Chunhua Shen;Ian Reid

  • Learning Markov Clustering Networks for Scene Text Detection

    Zichuan Liu;Guosheng Lin;Sheng Yang;Jiashi Feng

Frequent Co-Authors

Chunhua Shen
Chunhua Shen Zhejiang University
Ian Reid
Ian Reid University of Adelaide
Anton van den Hengel
Anton van den Hengel University of Adelaide
Jianfei Cai
Jianfei Cai Monash University
Steven C. H. Hoi
Steven C. H. Hoi Alibaba Group (China)
Weisi Lin
Weisi Lin Nanyang Technological University
Lingqiao Liu
Lingqiao Liu University of Adelaide
Henghui Ding
Henghui Ding Nanyang Technological University
David Suter
David Suter Edith Cowan University
Chunyan Miao
Chunyan Miao Nanyang Technological University

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