World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
58081
World Ranking
3713
National Ranking
221

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
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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