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D-Index
48
Citations
8705
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364
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121

Computer Science

D-Index
43
Citations
8665
World Ranking
7927
National Ranking
1041

Zuxuan Wu 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 Zuxuan Wu 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: 243 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Zuxuan Wu 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 Zuxuan Wu 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: 43 D-Index — 46th percentile

46% 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 Rising Stars Award

Overview

Zuxuan Wu is affiliated with Fudan University in China and has contributed extensively to the field of computer science, particularly in areas related to computer vision and artificial intelligence. Their research spans several subfields and topics within computer science, reflecting a broad and multidisciplinary approach to advanced machine learning applications.

The primary fields of study in Wu's work include:

  • Computer Science

Within this main field, the subfields of study are:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Signal Processing
  • Control and Systems Engineering
  • Neurology

Wu's research topics cover a variety of machine learning and computer vision challenges, including:

  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Adversarial Robustness in Machine Learning
  • Generative Adversarial Networks and Image Synthesis
  • Video Analysis and Summarization

Zuxuan Wu has published research in several high-profile venues frequently used in the computer vision and artificial intelligence communities. The most common publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Multimedia
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

The scientist has also been involved in book publication through Springer International Publishing with the title:

  • Deep Learning for Video Understanding (2024)

Wu's recent papers demonstrate involvement in topics such as domain adaptation, video transformers, image manipulation detection, 3D object detection, and adversarial attacks on vision transformers. Representative recent papers include:

  • Cross-Domain Contrastive Learning for Unsupervised Domain Adaptation, 2022, IEEE Transactions on Multimedia
  • BEVT: BERT Pretraining of Video Transformers, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • ObjectFormer for Image Manipulation Detection and Localization, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • M3DETR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers, 2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Towards Transferable Adversarial Attacks on Vision Transformers, 2022, Proceedings of the AAAI Conference on Artificial Intelligence

Frequent coauthors contributing alongside Wu include:

  • Yu-Gang Jiang
  • Jingjing Chen
  • Junke Wang
  • Larry S. Davis
  • Zejia Weng

Best Publications

  • VITON: An Image-Based Virtual Try-on Network

    Xintong Han;Zuxuan Wu;Zhe Wu;Ruichi Yu

  • Modeling Spatial-Temporal Clues in a Hybrid Deep Learning Framework for Video Classification

    Zuxuan Wu;Xi Wang;Yu-Gang Jiang;Hao Ye

  • Learning Fashion Compatibility with Bidirectional LSTMs

    Xintong Han;Zuxuan Wu;Yu-Gang Jiang;Larry S. Davis

  • BlockDrop: Dynamic Inference Paths in Residual Networks

    Zuxuan Wu;Tushar Nagarajan;Abhishek Kumar;Steven Rennie

  • Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks

    Yu-Gang Jiang;Zuxuan Wu;Jun Wang;Xiangyang Xue

  • M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection.

    Junke Wang;Zuxuan Wu;Jingjing Chen;Yu-Gang Jiang

  • DCAN: Dual Channel-Wise Alignment Networks for Unsupervised Scene Adaptation

    Zuxuan Wu;Xintong Han;Yen-Liang Lin;Mustafa Gökhan Uzunbas

  • Cross-Domain Contrastive Learning for Unsupervised Domain Adaptation

    Unknown

  • Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors

    Zuxuan Wu;Ser-Nam Lim;Larry S. Davis;Tom Goldstein

  • AdaFrame: Adaptive Frame Selection for Fast Video Recognition

    Zuxuan Wu;Caiming Xiong;Chih-Yao Ma;Richard Socher

  • Multi-Stream Multi-Class Fusion of Deep Networks for Video Classification

    Zuxuan Wu;Yu-Gang Jiang;Xi Wang;Hao Ye

  • Automatic Spatially-Aware Fashion Concept Discovery

    Xintong Han;Zuxuan Wu;Phoenix X. Huang;Xiao Zhang

  • BEVT: BERT Pretraining of Video Transformers.

    Rui Wang;Dongdong Chen;Zuxuan Wu;Yinpeng Chen

  • Self-Monitoring Navigation Agent via Auxiliary Progress Estimation

    Chih-Yao Ma;Jiasen Lu;Zuxuan Wu;Ghassan AlRegib

  • The Regretful Agent: Heuristic-Aided Navigation Through Progress Estimation

    Chih-Yao Ma;Zuxuan Wu;Ghassan AlRegib;Caiming Xiong

  • Exploring Inter-feature and Inter-class Relationships with Deep Neural Networks for Video Classification

    Zuxuan Wu;Yu-Gang Jiang;Jun Wang;Jian Pu

  • Deep learning for video classification and captioning

    Zuxuan Wu;Ting Yao;Yanwei Fu;Yu-Gang Jiang

  • OmniVL: One Foundation Model for Image-Language and Video-Language Tasks

    Unknown

  • Evaluating Two-Stream CNN for Video Classification

    Hao Ye;Zuxuan Wu;Rui-Wei Zhao;Xi Wang

  • M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers.

    Tianrui Guan;Jun Wang;Shiyi Lan;Rohan Chandra

  • Modeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification

    Yu-Gang Jiang;Zuxuan Wu;Jinhui Tang;Zechao Li

  • Harnessing Object and Scene Semantics for Large-Scale Video Understanding

    Zuxuan Wu;Yanwei Fu;Yu-Gang Jiang;Leonid Sigal

  • Self-Monitoring Navigation Agent via Auxiliary Progress Estimation

    Chih-Yao Ma;Jiasen Lu;Zuxuan Wu;Ghassan AlRegib

  • FLAG: Adversarial Data Augmentation for Graph Neural Networks

    Kezhi Kong;Guohao Li;Mucong Ding;Zuxuan Wu

Frequent Co-Authors

Yu-Gang Jiang
Yu-Gang Jiang Fudan University
Larry S. Davis
Larry S. Davis University of Maryland, College Park
Tom Goldstein
Tom Goldstein University of Maryland, College Park
Caiming Xiong
Caiming Xiong Salesforce (United States)
Xiangyang Xue
Xiangyang Xue Fudan University
Shih-Fu Chang
Shih-Fu Chang Columbia University
Abhinav Shrivastava
Abhinav Shrivastava University of Maryland, College Park
Serge Belongie
Serge Belongie University of Copenhagen
Claire Cardie
Claire Cardie Cornell University

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