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Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
97
Citations
33462
World Ranking
427
National Ranking
54

Liang 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 Liang Lin 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: 394 publications — 86th percentile

86% of scientists in this discipline score the same or lower.

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

Liang 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 Liang Lin 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: 97 D-Index — 97th percentile

97% 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
  • 2023 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in China Leader Award

Overview

Liang Lin is affiliated with Sun Yat-sen University in China and specializes in computer science, with a focus on subfields such as computer vision and pattern recognition, artificial intelligence, media technology, electrical and electronic engineering, and immunology.

The primary research topics associated with Liang Lin include:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Topic Modeling
  • Video Surveillance and Tracking Methods

The scientist has published extensively, contributing notably to venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Neural Networks and Learning Systems

Recent publications by Liang Lin include:

  • Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Physical-Virtual Collaboration Modeling for Intra- and Inter-Station Metro Ridership Prediction, 2020, IEEE Transactions on Intelligent Transportation Systems
  • Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction, 2020, IEEE Transactions on Intelligent Transportation Systems
  • Injecting Semantic Concepts into End-to-End Image Captioning, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Tree-Structured Policy Based Progressive Reinforcement Learning for Temporally Language Grounding in Video, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

Frequent coauthors collaborating with Liang Lin include:

  • Guanbin Li
  • Xiaodan Liang
  • Tianshui Chen
  • Yukai Shi
  • Pengxu Wei

Best Publications

  • NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

    Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang

  • Joint Detection and Identification Feature Learning for Person Search

    Tong Xiao;Shuang Li;Bochao Wang;Liang Lin

  • Is Faster R-CNN Doing Well for Pedestrian Detection?

    Liliang Zhang;Liang Lin;Xiaodan Liang;Kaiming He

  • Multi-level Wavelet-CNN for Image Restoration

    Pengju Liu;Hongzhi Zhang;Kai Zhang;Liang Lin

  • Deep feature learning with relative distance comparison for person re-identification

    Shengyong Ding;Liang Lin;Guangrun Wang;Hongyang Chao

  • Cost-Effective Active Learning for Deep Image Classification

    Keze Wang;Dongyu Zhang;Ya Li;Ruimao Zhang

  • SNAS: stochastic neural architecture search

    Sirui Xie;Hehui Zheng;Chunxiao Liu;Liang Lin

  • Unsupervised Image Super-Resolution Using Cycle-in-Cycle Generative Adversarial Networks

    Yuan Yuan;Siyuan Liu;Jiawei Zhang;Yongbing Zhang

  • Meta R-CNN: Towards General Solver for Instance-Level Low-Shot Learning

    Xiaopeng Yan;Ziliang Chen;Anni Xu;Xiaoxi Wang

  • Bit-Scalable Deep Hashing With Regularized Similarity Learning for Image Retrieval and Person Re-Identification

    Ruimao Zhang;Liang Lin;Rui Zhang;Wangmeng Zuo

  • Look into Person: Self-Supervised Structure-Sensitive Learning and a New Benchmark for Human Parsing

    Ke Gong;Xiaodan Liang;Dongyu Zhang;Xiaohui Shen

  • Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation

    Ruijia Xu;Guanbin Li;Jihan Yang;Liang Lin

  • Joint Learning of Single-Image and Cross-Image Representations for Person Re-identification

    Faqiang Wang;Wangmeng Zuo;Liang Lin;David Zhang

  • Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift

    Ruijia Xu;Ziliang Chen;Wangmeng Zuo;Junjie Yan

  • I2T: Image Parsing to Text Description

    Benjamin Z Yao;Xiong Yang;Liang Lin;Mun Wai Lee

  • Knowledge-Embedded Routing Network for Scene Graph Generation

    Tianshui Chen;Weihao Yu;Riquan Chen;Liang Lin

  • Semantic Object Parsing with Graph LSTM

    Xiaodan Liang;Xiaohui Shen;Jiashi Feng;Liang Lin

  • Toward Characteristic-Preserving Image-Based Virtual Try-On Network

    Bochao Wang;Huabin Zheng;Xiaodan Liang;Yimin Chen

  • Look into Person: Joint Body Parsing & Pose Estimation Network and a New Benchmark

    Xiaodan Liang;Ke Gong;Xiaohui Shen;Liang Lin

  • Learning Collaborative Sparse Representation for Grayscale-Thermal Tracking

    Chenglong Li;Hui Cheng;Shiyi Hu;Xiaobai Liu

  • Instance-Level Human Parsing via Part Grouping Network.

    Ke Gong;Xiaodan Liang;Yicheng Li;Yimin Chen

Frequent Co-Authors

Xiaodan Liang
Xiaodan Liang Sun Yat-sen University
Guanbin Li
Guanbin Li Sun Yat-sen University
Wangmeng Zuo
Wangmeng Zuo Harbin Institute of Technology
Shuicheng Yan
Shuicheng Yan National University of Singapore
Ping Luo
Ping Luo University of Hong Kong
Xiaohui Shen
Xiaohui Shen ByteDance
Lei Zhang
Lei Zhang Hong Kong Polytechnic University
Si Liu
Si Liu Beihang University
Yizhou Yu
Yizhou Yu University of Hong Kong
Xiaogang Wang
Xiaogang Wang Chinese University of Hong Kong

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