Joost van de Weijer

136 papers receiving 8.2k citations

Hit Papers

Adaptive Color Attributes for Real-Time Visual Tracking2007202620132019201420072009201120222505007501000

Peers

Joost van de Weijer
Comparison fields: 5 of 166
  • Computer Vision and Pattern Recognition 7.1k
  • Artificial Intelligence 1.7k
  • Media Technology 1.6k
  • Atomic and Molecular Physics, and Optics 1.3k
  • Aerospace Engineering 879
Replace Theo Gevers with:
Theo Gevers Netherlands
Sabine Süsstrunk Switzerland
Weisi Lin Singapore
In So Kweon South Korea
Shai Avidan Israel
Fatih Porikli Australia
Radu Timofte Switzerland
Jan‐Mark Geusebroek Netherlands
Jianbing Shen China
Jia‐Bin Huang United States
Joost van de Weijer relative to Theo Gevers Netherlands Theo Gevers's profile →
Citations per field
00.5×1.5×1.9×
Theo Gevers · 1×
Citations per year

Countries citing papers authored by Joost van de Weijer

Since Specialization
Citations

This map shows the geographic impact of Joost van de Weijer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Joost van de Weijer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joost van de Weijer more than expected).

Fields of papers citing papers by Joost van de Weijer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joost van de Weijer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Joost van de Weijer. The network helps show where Joost van de Weijer may publish in the future.

Co-authorship network of co-authors of Joost van de Weijer

This figure shows the co-authorship network connecting the top 25 collaborators of Joost van de Weijer. A scholar is included among the top collaborators of Joost van de Weijer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joost van de Weijer. Joost van de Weijer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 4
3 2
4 25
5 2
6 9
7 2
8 5
9
Class-incremental learning: survey and performance evaluation
46
10 236
11
Metric Learning for Novelty and Anomaly Detection.
4
12
Memory Replay GANs: Learning to Generate New Categories without Forgetting
115
13 203
14 10
15
Adaptive Color Attributes for Real-Time Visual Trackingbreakdown →
1104
16
The Dichromatic Reflection Model - Future Research Directions and Applications.
4
17 1
18 11
19
Linear and Robust Estimation of Local Image Structure
1
20
Curvature estimation from orientation fields
22

About Joost van de Weijer

Joost van de Weijer is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 139 papers that have together received 8.5k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (39 papers), Advanced Image and Video Retrieval Techniques (33 papers) and Image Enhancement Techniques (28 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (7.1k citations), Media Technology (1.6k citations) and Artificial Intelligence (1.7k citations). Joost van de Weijer has collaborated with scholars based in Spain, Netherlands and China. Frequent co-authors include Fahad Shahbaz Khan, Andrew D. Bagdanov, Arjan Gijsenij, Xialei Liu, Michael Felsberg, Martin Danelljan, Theo Gevers, Jakob Verbeek, Jan‐Mark Geusebroek and Cordelia Schmid. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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