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Computer Science
Spain
2025

D-Index & Metrics

Computer Science

D-Index
69
Citations
20580
World Ranking
1966
National Ranking
22

Research.com Recognitions

  • 2025 - Research.com Computer Science in Spain Leader Award
  • 2022 - Research.com Computer Science in Spain Leader Award

Overview

Joost van de Weijer is affiliated with the Autonomous University of Barcelona in Spain. Their research primarily focuses on the field of Computer Science, with specializations in Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Cancer Research, and Epidemiology.

The scientist's work engages with a range of main topics, including:

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Generative Adversarial Networks and Image Synthesis
  • COVID-19 diagnosis using AI
  • Machine Learning and ELM
  • Advanced Image and Video Retrieval Techniques

Recent publications by Joost van de Weijer include the following papers:

  • Class-Incremental Learning: Survey and Performance Evaluation on Image Classification (2022), IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Avalanche: An end-to-end library for continual learning (2021), CINECA IRIS Institutional research information system (University of Pisa)
  • Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation (2021), arXiv (Cornell University)
  • Class-incremental learning: survey and performance evaluation on image classification (2020), arXiv (Cornell University)
  • Self-Training for Class-Incremental Semantic Segmentation (2022), IEEE Transactions on Neural Networks and Learning Systems

The scientist frequently publishes in several venues, notably:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • International Journal of Computer Vision
  • Computer Vision and Image Understanding

Joost van de Weijer has collaborated with several researchers on numerous projects. Frequent co-authors include:

  • Bartłomiej Twardowski
  • Luis Herranz
  • Yaxing Wang
  • Kai Wang
  • Andrew D. Bagdanov

Best Publications

  • Adaptive Color Attributes for Real-Time Visual Tracking

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

  • Learning Color Names for Real-World Applications

    J. van de Weijer;C. Schmid;J. Verbeek;D. Larlus

  • Invertible Conditional GANs for image editing.

    Guim Perarnau;Joost van de Weijer;Bogdan Raducanu;Jose M. Álvarez

  • Computational Color Constancy: Survey and Experiments

    A. Gijsenij;T. Gevers;J. van de Weijer

  • The sixth visual object tracking VOT2018 challenge results

    Matej Kristan;Aleš Leonardis;Jiří Matas;Michael Felsberg

  • Coloring Local Feature Extraction

    Joost Van De Weijer;Cordelia Schmid

  • Class-incremental learning: survey and performance evaluation on image classification

    Marc Masana;Xialei Liu;Bartlomiej Twardowski;Mikel Menta

  • Fast anisotropic Gauss filtering

    J.-M. Geusebroek;A.W.M. Smeulders;J. van de Weijer

  • RankIQA: Learning from Rankings for No-Reference Image Quality Assessment

    Xialei Liu;Joost van de Weijer;Andrew D. Bagdanov

  • The Seventh Visual Object Tracking VOT2019 Challenge Results

    Matej Kristan;Amanda Berg;Linyu Zheng;Litu Rout

  • Boosting color saliency in image feature detection

    J. van de Weijer;T. Gevers;A.D. Bagdanov

  • 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

  • Color attributes for object detection

    Fahad Shahbaz Khan;Rao Muhammad Anwer;Joost van de Weijer;Andrew D. Bagdanov

  • Leveraging Unlabeled Data for Crowd Counting by Learning to Rank

    Xialei Liu;Joost van de Weijer;Andrew D. Bagdanov

  • Generalized Gamut Mapping using Image Derivative Structures for Color Constancy

    Arjan Gijsenij;Theo Gevers;Joost Weijer

  • Semantic Drift Compensation for Class-Incremental Learning

    Lu Yu;Bartlomiej Twardowski;Xialei Liu;Luis Herranz

  • Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

    Rao Muhammad Anwer;Fahad Shahbaz Khan;Joost van de Weijer;Matthieu Molinier

  • Transferring GANs: generating images from limited data

    Yaxing Wang;Chenshen Wu;Luis Herranz;Joost van de Weijer

  • Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting

    Xialei Liu;Marc Masana;Luis Herranz;Joost Van de Weijer

  • Learning Color Names from Real-World Images

    J. van de Weijer;C. Schmid;J. Verbeek

  • Class-incremental learning: survey and performance evaluation

    Marc Masana;Xialei Liu;Bartlomiej Twardowski;Mikel Menta

Frequent Co-Authors

Fahad Shahbaz Khan
Fahad Shahbaz Khan Mohamed bin Zayed University of Artificial Intelligence
Andrew D. Bagdanov
Andrew D. Bagdanov University of Florence
Theo Gevers
Theo Gevers University of Amsterdam
Antonio M. López
Antonio M. López Autonomous University of Barcelona
Michael Felsberg
Michael Felsberg Linköping University
Jan-Mark Geusebroek
Jan-Mark Geusebroek University of Amsterdam
Jorma Laaksonen
Jorma Laaksonen Aalto University
Frédéric Jurie
Frédéric Jurie Université de Caen Normandie
Joan Serrat
Joan Serrat Universitat Politècnica de Catalunya

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