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Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
67
Citations
38393
World Ranking
2135
National Ranking
67

Liang Zheng 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 Zheng 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: 136 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Liang Zheng 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 Zheng 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: 67 D-Index — 85th percentile

85% 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

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Liang Zheng is affiliated with the Australian National University in Australia and has an extensive publication record in the field of Computer Science. Their research primarily focuses on areas including Computer Vision and Pattern Recognition, Artificial Intelligence, Nuclear and High Energy Physics, Signal Processing, and Civil and Structural Engineering.

The main topics of Liang Zheng's work cover:

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

Frequently collaborating with other researchers, Liang Zheng has coauthored numerous publications alongside colleagues such as Stephen Jay Gould, Yunzhong Hou, Tom Gedeon, Weijian Deng, and Zhongdao Wang.

Their work has appeared in various academic venues, with a significant number published in:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • SSRN Electronic Journal
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Multimedia

Examples of recent papers by Liang Zheng include:

  • Random Erasing Data Augmentation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Learning to Adapt Invariance in Memory for Person Re-identification, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Category-Level Adversarial Adaptation for Semantic Segmentation using Purified Features, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Circle Loss: A Unified Perspective of Pair Similarity Optimization, 2020, arXiv (Cornell University)
  • Rethinking Triplet Loss for Domain Adaptation, 2020, IEEE Transactions on Circuits and Systems for Video Technology

Liang Zheng's work addresses several domains related to machine learning and computer vision. The emphasis on domain adaptation and neural network optimization techniques reflects ongoing exploration of methods to improve model performance across different datasets and learning scenarios.

Best Publications

  • Scalable Person Re-identification: A Benchmark

    Liang Zheng;Liang Zheng;Liyue Shen;Lu Tian;Shengjin Wang

  • Random Erasing Data Augmentation

    Zhun Zhong;Liang Zheng;Guoliang Kang;Shaozi Li

  • Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline)

    Yifan Sun;Liang Zheng;Yi Yang;Qi Tian

  • Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in Vitro

    Zhedong Zheng;Liang Zheng;Yi Yang

  • Re-ranking Person Re-identification with k-Reciprocal Encoding

    Zhun Zhong;Liang Zheng;Donglin Cao;Shaozi Li

  • Person Re-identification: Past, Present and Future

    Liang Zheng;Yi Yang;Alexander G. Hauptmann

  • MARS: A Video Benchmark for Large-Scale Person Re-Identification

    Liang Zheng;Liang Zheng;Zhi Bie;Yifan Sun;Jingdong Wang

  • Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification

    Weijian Deng;Liang Zheng;Qixiang Ye;Guoliang Kang

  • Towards Real-Time Multi-Object Tracking

    Zhongdao Wang;Liang Zheng;Yixuan Liu;Yali Li

  • A Discriminatively Learned CNN Embedding for Person Reidentification

    Zhedong Zheng;Liang Zheng;Yi Yang

  • Circle Loss: A Unified Perspective of Pair Similarity Optimization

    Yifan Sun;Changmao Cheng;Yuhan Zhang;Chi Zhang

  • Improving person re-identification by attribute and identity learning

    Yutian Lin;Liang Zheng;Zhedong Zheng;Yu Wu

  • Person Re-identification in the Wild

    Liang Zheng;Hengheng Zhang;Shaoyan Sun;Manmohan Chandraker

  • Joint Discriminative and Generative Learning for Person Re-Identification

    Zhedong Zheng;Xiaodong Yang;Zhiding Yu;Liang Zheng

  • SVDNet for Pedestrian Retrieval

    Yifan Sun;Liang Zheng;Weijian Deng;Shengjin Wang

  • SIFT Meets CNN: A Decade Survey of Instance Retrieval

    Liang Zheng;Yi Yang;Qi Tian

  • Taking a Closer Look at Domain Shift: Category-Level Adversaries for Semantics Consistent Domain Adaptation

    Yawei Luo;Liang Zheng;Tao Guan;Junqing Yu

  • Unsupervised Person Re-identification: Clustering and Fine-tuning

    Hehe Fan;Liang Zheng;Chenggang Yan;Yi Yang

  • Camera Style Adaptation for Person Re-identification

    Zhun Zhong;Liang Zheng;Zhedong Zheng;Shaozi Li

  • Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-Identification

    Zhun Zhong;Liang Zheng;Zhiming Luo;Shaozi Li

Frequent Co-Authors

Shengjin Wang
Shengjin Wang Tsinghua University
Qi Tian
Qi Tian Huawei Technologies (China)
Zhedong Zheng
Zhedong Zheng University of Macau
Zhun Zhong
Zhun Zhong Hefei University of Technology
Shaozi Li
Shaozi Li Xiamen University
Xiaodong Yang
Xiaodong Yang Nvidia (United Kingdom)
Jianbin Jiao
Jianbin Jiao University of Chinese Academy of Sciences
Jingdong Wang
Jingdong Wang Baidu (China)
Stephen Gould
Stephen Gould Australian National University
Milind R. Naphade
Milind R. Naphade Nvidia (United States)

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