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Martin Danelljan

Martin Danelljan

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Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
52
Citations
30085
World Ranking
261
National Ranking
3

Computer Science

D-Index
52
Citations
32306
World Ranking
4938
National Ranking
103

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Martin Danelljan is affiliated with ETH Zurich in Switzerland and has a substantial body of research in computer science, focusing primarily on computer vision and related subfields.

Their main fields of study include:

  • Computer Science

Their work spans several subfields such as:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Media Technology
  • Aerospace Engineering
  • Computer Graphics and Computer-Aided Design

The core topics covered by Martin Danelljan's research include:

  • Advanced Neural Network Applications
  • Video Surveillance and Tracking Methods
  • Visual Attention and Saliency Detection
  • Advanced Image Processing Techniques
  • Advanced Image and Video Retrieval Techniques
  • Domain Adaptation and Few-Shot Learning
  • Advanced Vision and Imaging

Recent papers authored or co-authored by Martin Danelljan include:

  • "RePaint: Inpainting using Denoising Diffusion Probabilistic Models" (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR))
  • "Transforming Model Prediction for Tracking" (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR))
  • "Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook" (2022, IEEE Transactions on Pattern Analysis and Machine Intelligence)
  • "Segment Anything in High Quality" (2023, arXiv (Cornell University))
  • "Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling" (2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV))

Frequent co-authors collaborating with Martin Danelljan are:

  • Luc Van Gool
  • Radu Timofte
  • Fisher Yu
  • Goutam Bhat
  • Michael Felsberg

Martin Danelljan's publications have appeared in various venues, including:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Lecture notes in computer science
  • Repository for Publications and Research Data (ETH Zurich)

Best Publications

  • ECO: Efficient Convolution Operators for Tracking

    Martin Danelljan;Goutam Bhat;Fahad Shahbaz Khan;Michael Felsberg

  • Accurate scale estimation for robust visual tracking

    Martin Danelljan;Gustav Häger;Fahad Shahbaz Khan;Michael Felsberg

  • Learning Spatially Regularized Correlation Filters for Visual Tracking

    Martin Danelljan;Gustav Hager;Fahad Shahbaz Khan;Michael Felsberg

  • Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking

    Martin Danelljan;Andreas Robinson;Fahad Shahbaz Khan;Michael Felsberg

  • The Visual Object Tracking VOT2016 Challenge Results

    Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg

  • The Visual Object Tracking VOT2017 Challenge Results

    Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg

  • Adaptive Color Attributes for Real-Time Visual Tracking

    Martin Danelljan;Fahad Shahbaz Khan;Michael Felsberg;Joost van de Weijer

  • The Visual Object Tracking VOT2015 Challenge Results

    Matej Kristan;Jiri Matas;Ale Leonardis;Michael Felsberg

  • Discriminative Scale Space Tracking

    Martin Danelljan;Gustav Hager;Fahad Shahbaz Khan;Michael Felsberg

  • ATOM: Accurate Tracking by Overlap Maximization

    Martin Danelljan;Goutam Bhat;Fahad Shahbaz Khan;Michael Felsberg

  • Learning Discriminative Model Prediction for Tracking

    Goutam Bhat;Martin Danelljan;Luc Van Gool;Radu Timofte

  • Convolutional Features for Correlation Filter Based Visual Tracking

    Martin Danelljan;Gustav Hager;Fahad Shahbaz Khan;Michael Felsberg

  • The sixth visual object tracking VOT2018 challenge results

    Matej Kristan;Aleš Leonardis;Jiří Matas;Michael Felsberg

  • Probabilistic Regression for Visual Tracking

    Martin Danelljan;Luc Van Gool;Radu Timofte

  • Unveiling the Power of Deep Tracking

    Goutam Bhat;Joakim Johnander;Martin Danelljan;Fahad Shahbaz Khan

  • The Seventh Visual Object Tracking VOT2019 Challenge Results

    Matej Kristan;Amanda Berg;Linyu Zheng;Litu Rout

  • Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking

    Martin Danelljan;Gustav Hager;Fahad Shahbaz Khan;Michael Felsberg

  • Learning the Model Update for Siamese Trackers

    Lichao Zhang;Abel Gonzalez-Garcia;Joost Van De Weijer;Martin Danelljan

  • The Visual Object Tracking VOT2014 challenge results

    Matej Kristan;Roman P. Pflugfelder;Ales Leonardis;Jiri Matas

  • Deep Projective 3D Semantic Segmentation

    Felix Järemo Lawin;Martin Danelljan;Patrik Tosteberg;Goutam Bhat

  • SRFlow: Learning the Super-Resolution Space with Normalizing Flow

    Andreas Lugmayr;Martin Danelljan;Luc Van Gool;Radu Timofte

Frequent Co-Authors

Radu Timofte
Radu Timofte University of Wurzburg
Fahad Shahbaz Khan
Fahad Shahbaz Khan Mohamed bin Zayed University of Artificial Intelligence
Michael Felsberg
Michael Felsberg Linköping University
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Thomas B. Schön
Thomas B. Schön Uppsala University
Joost van de Weijer
Joost van de Weijer Autonomous University of Barcelona
Matej Kristan
Matej Kristan University of Ljubljana
Philip H. S. Torr
Philip H. S. Torr University of Oxford
Christian Micheloni
Christian Micheloni University of Udine
Fisher Yu
Fisher Yu ETH Zurich

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