World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
38153
World Ranking
4172
National Ranking
561

Jifeng Dai 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 Jifeng Dai 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 103 publications — 9th percentile

9% of scientists in this discipline score the same or lower.

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

Jifeng Dai 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 Jifeng Dai sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Jifeng Dai is affiliated with Tsinghua University in China and has made significant contributions to the field of computer science, particularly within computer vision and pattern recognition. Their research spans several subfields, including artificial intelligence, cardiology and cardiovascular medicine, aerospace engineering, and electrical and electronic engineering.

The scientist's research focuses on several key topics:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Topic Modeling
  • Natural Language Processing Techniques
  • Advanced Vision and Imaging

Jifeng Dai has published extensively in high-impact venues, collaborating frequently with researchers such as Yu Qiao, Xizhou Zhu, Hongsheng Li, Lewei Lu, and Wenhai Wang. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Science China Information Sciences

Some recent papers authored or co-authored by Jifeng Dai include:

  • Deformable DETR: Deformable Transformers for End-to-End Object Detection (2020, arXiv)
  • MMDetection: Open MMLab Detection Toolbox and Benchmark (2024, arXiv)
  • Exploring Cross-Image Pixel Contrast for Semantic Segmentation (2021, 2021 IEEE/CVF International Conference on Computer Vision)
  • Fast Convergence of DETR with Spatially Modulated Co-Attention (2021, 2021 IEEE/CVF International Conference on Computer Vision)
  • Vision Transformer Adapter for Dense Predictions (2022, arXiv)

The scientist's work involves developing advanced neural network architectures, including transformers adapted for vision tasks, and exploring novel methods for object detection and semantic segmentation. Their contributions span both theoretical developments and practical implementations in machine learning toolboxes.

Overall, Jifeng Dai's research portfolio demonstrates a blend of interdisciplinary scientific inquiry and focused expertise in advanced computational techniques within computer science, particularly addressing challenges in visual data processing and multimodal learning.

Best Publications

  • Deformable Convolutional Networks

    Jifeng Dai;Haozhi Qi;Yuwen Xiong;Yi Li

  • R-FCN: Object Detection via Region-based Fully Convolutional Networks

    Jifeng Dai;Yi Li;Kaiming He;Jian Sun

  • Deformable DETR: Deformable Transformers for End-to-End Object Detection

    Xizhou Zhu;Weijie Su;Lewei Lu;Bin Li

  • Deformable ConvNets V2: More Deformable, Better Results

    Xizhou Zhu;Han Hu;Stephen Lin;Jifeng Dai

  • Instance-Aware Semantic Segmentation via Multi-task Network Cascades

    Jifeng Dai;Kaiming He;Jian Sun

  • Relation Networks for Object Detection

    Han Hu;Jiayuan Gu;Zheng Zhang;Jifeng Dai

  • BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation

    Jifeng Dai;Kaiming He;Jian Sun

  • ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation

    Di Lin;Jifeng Dai;Jiaya Jia;Kaiming He

  • Fully Convolutional Instance-Aware Semantic Segmentation

    Yi Li;Haozhi Qi;Jifeng Dai;Xiangyang Ji

  • InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

    Unknown

  • VL-BERT: Pre-training of Generic Visual-Linguistic Representations

    Weijie Su;Xizhou Zhu;Yue Cao;Bin Li

  • MMDetection: Open MMLab Detection Toolbox and Benchmark.

    Kai Chen;Jiaqi Wang;Jiangmiao Pang;Yuhang Cao

  • Deep Feature Flow for Video Recognition

    Xizhou Zhu;Yuwen Xiong;Jifeng Dai;Lu Yuan

  • Flow-Guided Feature Aggregation for Video Object Detection

    Xizhou Zhu;Yujie Wang;Jifeng Dai;Lu Yuan

  • Planning-oriented Autonomous Driving

    Unknown

  • An Empirical Study of Spatial Attention Mechanisms in Deep Networks

    Xizhou Zhu;Dazhi Cheng;Zheng Zhang;Stephen Lin

  • Exploring Cross-Image Pixel Contrast for Semantic Segmentation

    Wenguan Wang;Tianfei Zhou;Fisher Yu;Jifeng Dai

  • Convolutional feature masking for joint object and stuff segmentation

    Jifeng Dai;Kaiming He;Jian Sun

  • BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

    Unknown

  • Instance-Sensitive Fully Convolutional Networks

    Jifeng Dai;Kaiming He;Yi Li;Shaoqing Ren

  • Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation

    Guolei Sun;Wenguan Wang;Jifeng Dai;Jifeng Dai;Luc Van Gool

  • Towards High Performance Video Object Detection

    Xizhou Zhu;Jifeng Dai;Lu Yuan;Yichen Wei

  • Fast Convergence of DETR with Spatially Modulated Co-Attention

    Peng Gao;Minghang Zheng;Xiaogang Wang;Jifeng Dai

Frequent Co-Authors

Yichen Wei
Yichen Wei Microsoft Research Asia (China)
Kaiming He
Kaiming He Facebook (United States)
Jian Sun
Jian Sun Megvii
Han Hu
Han Hu Microsoft Research Asia (China)
Hongsheng Li
Hongsheng Li Chinese University of Hong Kong
Lu Yuan
Lu Yuan Microsoft (United States)
Wenguan Wang
Wenguan Wang Zhejiang University
Gao Huang
Gao Huang Tsinghua University
Ying Nian Wu
Ying Nian Wu University of California, Los Angeles
Stephen Lin
Stephen Lin Microsoft Research Asia (China)

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