World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
58081
World Ranking
3713
National Ranking
220

Krystian Mikolajczyk 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 Krystian Mikolajczyk 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: 184 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Krystian Mikolajczyk 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 Krystian Mikolajczyk 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: 57 D-Index — 74th percentile

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

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

Overview

Krystian Mikolajczyk is affiliated with Imperial College London in the United Kingdom. Their research spans multiple areas within computer science and engineering, with a focus on image and video processing as well as neural network applications.

The main fields of study for Mikolajczyk include:

  • Computer Science
  • Engineering

Within these broad fields, the scientist's work covers several subfields such as:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Aerospace Engineering
  • Media Technology

Research topics addressed in their publications include:

  • Advanced Image and Video Retrieval Techniques
  • Advanced Vision and Imaging
  • Robotics and Sensor-Based Localization
  • Advanced Neural Network Applications
  • Image Processing Techniques and Applications
  • Human Pose and Action Recognition
  • Advanced Data Compression Techniques

Krystian Mikolajczyk has contributed extensively to international scientific venues, frequently publishing in:

  • arXiv (Cornell University)
  • IEEE Transactions on Wireless Communications
  • International Journal of Computer Vision
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Lecture notes in computer science

Co-authorship has played an important role in their career, with frequent collaborators including:

  • Denız Gündüz
  • Vassileios Balntas
  • Tony Ng
  • Yulin Shao
  • Roy Miles

Among recent publications, the following papers illustrate some of the core research directions:

  • Wireless Image Retrieval at the Edge, 2021, IRIS UNIMORE (University of Modena and Reggio Emilia)
  • Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters Revisited, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Channel-Adaptive Wireless Image Transmission With OFDM, 2022, IEEE Wireless Communications Letters
  • [Formula: see text]-Patches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors., 2020, PubMed
  • Deep Joint Source-Channel Coding for Adaptive Image Transmission Over MIMO Channels, 2024, IEEE Transactions on Wireless Communications

Best Publications

  • A performance evaluation of local descriptors

    K. Mikolajczyk;C. Schmid

  • A performance evaluation of local descriptors

    K. Mikolajczyk;C. Schmid

  • Scale & Affine Invariant Interest Point Detectors

    Krystian Mikolajczyk;Cordelia Schmid

  • A Comparison of Affine Region Detectors

    K. Mikolajczyk;T. Tuytelaars;C. Schmid;A. Zisserman

  • Tracking-Learning-Detection

    Z. Kalal;K. Mikolajczyk;J. Matas

  • Local Invariant Feature Detectors: A Survey

    Tinne Tuytelaars;Krystian Mikolajczyk

  • An Affine Invariant Interest Point Detector

    K. Mikolajczyk;C. Schmid

  • The Visual Object Tracking VOT2016 Challenge Results

    Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg

  • Indexing based on scale invariant interest points

    K. Mikolajczyk;C. Schmid

  • P-N learning: Bootstrapping binary classifiers by structural constraints

    Zdenek Kalal;Jiri Matas;Krystian Mikolajczyk

  • Forward-Backward Error: Automatic Detection of Tracking Failures

    Zdenek Kalal;Krystian Mikolajczyk;Jiri Matas

  • Human Detection Based on a Probabilistic Assembly of Robust Part Detectors

    Krystian Mikolajczyk;Cordelia Schmid;Andrew Zisserman

  • HPatches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors

    Vassileios Balntas;Karel Lenc;Andrea Vedaldi;Krystian Mikolajczyk

  • Learning local feature descriptors with triplets and shallow convolutional neural networks.

    Vassileios Balntas;Edgar Riba;Daniel Ponsa;Krystian Mikolajczyk

  • Deep correlation for matching images and text

    Fei Yan;Krystian Mikolajczyk

  • The MediaMill TRECVID 2009 Semantic Video Search Engine

    C.G.M. Snoek;K.E.A. van de Sande;O. de Rooij;B. Huurnink

  • The MediaMill TRECVID 2008 Semantic Video Search Engine

    C.G.M. Snoek;K.E.A. van de Sande;O. de Rooij;B. Huurnink

  • Evaluation of local detectors and descriptors for fast feature matching

    Ondrej Miksik;Krystian Mikolajczyk

  • Multiple Object Class Detection with a Generative Model

    K. Mikolajczyk;B. Leibe;B. Schiele

  • Local features for object class recognition

    K. Mikolajczyk;B. Leibe;B. Schiele

Frequent Co-Authors

Josef Kittler
Josef Kittler University of Surrey
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Jiri Matas
Jiri Matas Czech Technical University in Prague
Andrew Zisserman
Andrew Zisserman University of Oxford
Piotr Koniusz
Piotr Koniusz University of New South Wales
Muhammad Awais
Muhammad Awais University of Surrey
Bastian Leibe
Bastian Leibe RWTH Aachen University
Bernt Schiele
Bernt Schiele Max Planck Institute for Informatics
Andrea Vedaldi
Andrea Vedaldi University of Oxford
Deniz Gunduz
Deniz Gunduz Imperial College London

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