World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
58
Citations
14885
World Ranking
3601
National Ranking
479

Shiqi Wang 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 Shiqi Wang 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: 301 publications — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Shiqi Wang 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 Shiqi Wang 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: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Overview

Shiqi Wang is affiliated with the City University of Hong Kong in China and has a significant body of work in the field of Computer Science, with a strong focus on Computer Vision and Pattern Recognition. Their research contributions span several subfields including Artificial Intelligence, Signal Processing, Media Technology, and Electrical and Electronic Engineering.

The scientist has explored a range of topics within advanced image processing techniques. Key areas of work include image and video quality assessment, advanced data compression techniques, image enhancement techniques, video coding and compression technologies, advanced vision and imaging, and face recognition and analysis.

Shiqi Wang's recent research publications include studies published in prominent venues such as IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing. Notable papers include:

  • Image Quality Assessment: Unifying Structure and Texture Similarity, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Sparse Gradient Regularized Deep Retinex Network for Robust Low-Light Image Enhancement, 2021, IEEE Transactions on Image Processing
  • Single Image Deraining: From Model-Based to Data-Driven and Beyond, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Band Representation-Based Semi-Supervised Low-Light Image Enhancement: Bridging the Gap Between Signal Fidelity and Perceptual Quality, 2021, IEEE Transactions on Image Processing
  • Towards Unsupervised Deep Image Enhancement With Generative Adversarial Network, 2020, IEEE Transactions on Image Processing

Throughout their career, Shiqi Wang has collaborated frequently with several researchers, including Sam Kwong, Baoliang Chen, Haoliang Li, Wenhan Yang, and Meng Wang. These collaborations have contributed to a body of work with a high level of interdisciplinary engagement and depth.

The scientist has published extensively in several venues. The most common publication outlets include:

  • arXiv (Cornell University)
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Multimedia
  • SSRN Electronic Journal

Shiqi Wang's research is situated at the intersection of theoretical and applied aspects of image processing and computer vision, leveraging data-driven methods and signal processing techniques to address challenges in image enhancement, quality assessment, and related computational imaging domains.

Best Publications

  • Domain Generalization with Adversarial Feature Learning

    Haoliang Li;Sinno Jialin Pan;Shiqi Wang;Alex C. Kot

  • Image Quality Assessment: Unifying Structure and Texture Similarity.

    Keyan Ding;Kede Ma;Shiqi Wang;Eero P. Simoncelli

  • Sparse Gradient Regularized Deep Retinex Network for Robust Low-Light Image Enhancement

    Wenhan Yang;Wenjing Wang;Haofeng Huang;Shiqi Wang

  • From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement

    Wenhan Yang;Shiqi Wang;Yuming Fang;Yue Wang

  • A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images

    Shiqi Wang;Kede Ma;Hojatollah Yeganeh;Zhou Wang

  • Image and Video Compression With Neural Networks: A Review

    Siwei Ma;Xinfeng Zhang;Chuanmin Jia;Zhenghui Zhao

  • VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild

    Yihang Lou;Yan Bai;Jun Liu;Shiqi Wang

  • Saliency-Guided Quality Assessment of Screen Content Images

    Ke Gu;Shiqi Wang;Huan Yang;Weisi Lin

  • Single Image Deraining: From Model-Based to Data-Driven and Beyond

    Wenhan Yang;Robby T. Tan;Shiqi Wang;Yuming Fang

  • Group-Sensitive Triplet Embedding for Vehicle Reidentification

    Yan Bai;Yihang Lou;Feng Gao;Shiqi Wang

  • Unsupervised Domain Adaptation for Face Anti-Spoofing

    Haoliang Li;Wen Li;Hong Cao;Shiqi Wang

  • SSIM-Motivated Rate-Distortion Optimization for Video Coding

    Shiqi Wang;A. Rehman;Zhou Wang;Siwei Ma

  • Blind Quality Assessment of Tone-Mapped Images Via Analysis of Information, Naturalness, and Structure

    Ke Gu;Shiqi Wang;Guangtao Zhai;Siwei Ma

  • Comparison of Image Quality Models for Optimization of Image Processing Systems

    Keyan Ding;Kede Ma;Shiqi Wang;Eero P. Simoncelli

  • Band Representation-Based Semi-Supervised Low-Light Image Enhancement: Bridging the Gap Between Signal Fidelity and Perceptual Quality

    Wenhan Yang;Shiqi Wang;Yuming Fang;Yue Wang

  • Learning Generalized Deep Feature Representation for Face Anti-Spoofing

    Haoliang Li;Peisong He;Shiqi Wang;Anderson Rocha

  • Embedding Adversarial Learning for Vehicle Re-Identification

    Yihang Lou;Yan Bai;Jun Liu;Shiqi Wang

  • Content-Aware Convolutional Neural Network for In-Loop Filtering in High Efficiency Video Coding

    Chuanmin Jia;Shiqi Wang;Xinfeng Zhang;Shanshe Wang

  • Quality Prediction of Asymmetrically Distorted Stereoscopic 3D Images

    Jiheng Wang;Abdul Rehman;Kai Zeng;Shiqi Wang

  • Analysis of Distortion Distribution for Pooling in Image Quality Prediction

    Ke Gu;Shiqi Wang;Guangtao Zhai;Weisi Lin

  • No-Reference and Robust Image Sharpness Evaluation Based on Multiscale Spatial and Spectral Features

    Leida Li;Wenhan Xia;Weisi Lin;Yuming Fang

  • Comparison of Full-Reference Image Quality Models for Optimization of Image Processing Systems

    Keyan Ding;Kede Ma;Shiqi Wang;Eero P. Simoncelli

Frequent Co-Authors

Siwei Ma
Siwei Ma Peking University
Wen Gao
Wen Gao Peking University
Sam Kwong
Sam Kwong Lingnan University
Ling-Yu Duan
Ling-Yu Duan Peking University
Weisi Lin
Weisi Lin Nanyang Technological University
Alex C. Kot
Alex C. Kot Nanyang Technological University
Wenhan Yang
Wenhan Yang Peking University
Ke Gu
Ke Gu Beijing University of Technology
Zhou Wang
Zhou Wang University of Waterloo
Tiejun Huang
Tiejun Huang Peking University

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