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Nikos Komodakis

Nikos Komodakis

D-Index & Metrics

Computer Science

D-Index
52
Citations
26610
World Ranking
4944
National Ranking
24

Overview

Nikos Komodakis is a researcher affiliated with the University of Crete in Greece. Their academic work primarily focuses on the broad field of Computer Science, with a particular emphasis on areas within Computer Vision and Pattern Recognition and Artificial Intelligence.

The researcher has contributed extensively to several subfields, including Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, and Radiation. Their work spans topics such as Advanced Image and Video Retrieval Techniques, Multimodal Machine Learning Applications, Advanced Neural Network Applications, Domain Adaptation and Few-Shot Learning, Medical Imaging Techniques and Applications, Advanced X-ray and CT Imaging, and Medical Image Segmentation Techniques.

Nikos Komodakis has published numerous papers in various scientific venues. Frequent publication platforms include:

  • arXiv (Cornell University)
  • Remote Sensing
  • Information Processing & Management
  • Lecture Notes in Computer Science
  • Radiotherapy and Oncology

Their recent papers include:

  • "MARE: Self-Supervised Multi-Attention REsu-Net for Semantic Segmentation in Remote Sensing," 2021, Remote Sensing
  • "Self-supervised learning for medieval handwriting identification: A case study from the Vatican Apostolic Library," 2022, Information Processing & Management
  • "What to Hide from Your Students: Attention-Guided Masked Image Modeling," 2022, arXiv (Cornell University)
  • "DINO-Foresight: Looking into the Future with DINO," 2024, arXiv (Cornell University)
  • "Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers," 2025, arXiv (Cornell University)

Collaborations form an important part of their research activities. Nikos Komodakis frequently collaborates with other researchers, including:

  • Spyros Gidaris
  • Ioannis Kakogeorgiou
  • Nikos Paragios
  • Andrei Bursuc
  • Κωνσταντίνος Καράντζαλος

Best Publications

  • Wide Residual Networks

    Sergey Zagoruyko;Nikos Komodakis

  • Unsupervised Representation Learning by Predicting Image Rotations

    Spyros Gidaris;Praveer Singh;Nikos Komodakis

  • Paying more attention to attention: improving the performance of convolutional neural networks via attention transfer

    Sergey Zagoruyko;Nikos Komodakis

  • Learning to compare image patches via convolutional neural networks

    Sergey Zagoruyko;Nikos Komodakis

  • Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs

    Martin Simonovsky;Nikos Komodakis

  • Dynamic Few-Shot Visual Learning Without Forgetting

    Spyros Gidaris;Nikos Komodakis

  • Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model

    Spyros Gidaris;Nikos Komodakis

  • GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders

    Martin Simonovsky;Nikos Komodakis

  • Dense image registration through MRFs and efficient linear programming.

    Ben Glocker;Nikos Komodakis;Nikos Komodakis;Georgios Tziritas;Nassir Navab

  • Image Completion Using Efficient Belief Propagation Via Priority Scheduling and Dynamic Pruning

    N. Komodakis;G. Tziritas

  • Playing with Duality: An overview of recent primal?dual approaches for solving large-scale optimization problems

    Nikos Komodakis;Jean-Christophe Pesquet

  • MRF Energy Minimization and Beyond via Dual Decomposition

    N Komodakis;N Paragios;G Tziritas

  • Boosting Few-Shot Visual Learning With Self-Supervision

    Spyros Gidaris;Andrei Bursuc;Nikos Komodakis;Patrick Perez Perez

  • MRF Optimization via Dual Decomposition: Message-Passing Revisited

    N. Komodakis;N. Paragios;G. Tziritas

  • Image Completion Using Global Optimization

    N. Komodakis

  • Approximate Labeling via Graph Cuts Based on Linear Programming

    N. Komodakis;G. Tziritas

  • Building detection in very high resolution multispectral data with deep learning features

    M. Vakalopoulou;K. Karantzalos;N. Komodakis;N. Paragios

  • Markov Random Field modeling, inference & learning in computer vision & image understanding: A survey

    Chaohui Wang;Nikos Komodakis;Nikos Komodakis;Nikos Paragios;Nikos Paragios

  • A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems

    Jorg H. Kappes;Bjoern Andres;Fred A. Hamprecht;Christoph Schnorr

  • Fast, Approximately Optimal Solutions for Single and Dynamic MRFs

    N. Komodakis;G. Tziritas;N. Paragios

  • Generating Classification Weights With GNN Denoising Autoencoders for Few-Shot Learning

    Spyros Gidaris;Nikos Komodakis

Frequent Co-Authors

Nikos Paragios
Nikos Paragios CentraleSupélec
Georgios Tziritas
Georgios Tziritas University of Crete
Ben Glocker
Ben Glocker Imperial College London
Nassir Navab
Nassir Navab Technical University of Munich
Georg Langs
Georg Langs Medical University of Vienna
Sebastian Nowozin
Sebastian Nowozin Microsoft (United States)
Carsten Rother
Carsten Rother Heidelberg University
Dhruv Batra
Dhruv Batra Georgia Institute of Technology
Fred A. Hamprecht
Fred A. Hamprecht Heidelberg University

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