2026 Ondrej Chum: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	43	7732	7509	13	12	98	27934

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Computer Science

7732

7509

27934

Overview

Ondrej Chum is affiliated with the Czech Technical University in Prague in the Czech Republic. The primary field of study is computer science, with a focus on several subfields including computer vision and pattern recognition, artificial intelligence, aerospace engineering, media technology, and signal processing.

The scientist's research topics cover various areas such as:

Advanced Image and Video Retrieval Techniques
Domain Adaptation and Few-Shot Learning
Image Retrieval and Classification Techniques
Robotics and Sensor-Based Localization
Video Surveillance and Tracking Methods
Multimodal Machine Learning Applications
Advanced Vision and Imaging

Recent publications include:

"Minimal Solvers for Rectifying From Radially-Distorted Conjugate Translations," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
"Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales," 2020, International Journal of Computer Vision
"Learning and Aggregating Deep Local Descriptors for Instance-Level Recognition," 2020, Lecture Notes in Computer Science
"Edge Augmentation for Large-Scale Sketch Recognition without Sketches," 2022, 2022 26th International Conference on Pattern Recognition (ICPR)
"The 2021 Image Similarity Dataset and Challenge," 2021, arXiv (Cornell University)

Frequently collaborating co-authors are:

Giorgos Tolias
Nikos Efthymiadis
Nikolaos-Antonios Ypsilantis
Tomás Jenícek
Yannis Avrithis

Publication venues where Ondrej Chum has appeared multiple times include:

arXiv (Cornell University)
2022 26th International Conference on Pattern Recognition (ICPR)
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Lecture Notes in Computer Science

Best Publications

Robust wide-baseline stereo from maximally stable extremal regions

Jiri Matas;Ondrej Chum;Martin Urban;Tomás Pajdla

6575
Citations
Object retrieval with large vocabularies and fast spatial matching

J. Philbin;O. Chum;M. Isard;J. Sivic

3745
Citations
Lost in quantization: Improving particular object retrieval in large scale image databases

J. Philbin;O. Chum;M. Isard;J. Sivic

1909
Citations
Matching with PROSAC - progressive sample consensus

O. Chum;J. Matas

1528
Citations
Fine-Tuning CNN Image Retrieval with No Human Annotation

Filip Radenovic;Giorgos Tolias;Ondrej Chum

1335
Citations
Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval

O. Chum;J. Philbin;J. Sivic;M. Isard

1099
Citations
Locally Optimized RANSAC

Ondřej Chum;Jiří Matas;Jiří Matas;Josef Kittler

1049
Citations
Robust wide baseline stereo from maximally stable extremal regions

Jiri Matas;Ondrej Chum;Martin Urban;Tomás Pajdla

1039
Citations
USAC: A Universal Framework for Random Sample Consensus

R. Raguram;O. Chum;M. Pollefeys;J. Matas

711
Citations
CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples

Filip Radenović;Giorgos Tolias;Ondřej Chum

674
Citations
Near Duplicate Image Detection: min-Hash and tf-idf Weighting.

Ondrej Chum;James Philbin;Andrew Zisserman

624
Citations
Label Propagation for Deep Semi-Supervised Learning

Ahmet Iscen;Giorgos Tolias;Yannis Avrithis;Ondrej Chum

595
Citations
Optimal Randomized RANSAC

O. Chum;J. Matas

576
Citations
Negative Evidences and Co-occurences in Image Retrieval: The Benefit of PCA and Whitening

Hervé Jégou;Ondřej Chum

479
Citations
An Exemplar Model for Learning Object Classes

O. Chum;A. Zisserman

384
Citations
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking

Filip Radenovic;Ahmet Iscen;Giorgos Tolias;Yannis Avrithis

379
Citations
Total recall II: Query expansion revisited

Ondrej Chum;Andrej Mikulik;Michal Perdoch;Jiri Matas

358
Citations
Geometric min-Hashing: Finding a (thick) needle in a haystack

Ondrej Chum;Michal Perdoch;Jiri Matas

354
Citations
Efficient representation of local geometry for large scale object retrieval

Michal Perd'och;Ondrej Chum;Jiri Matas

347
Citations
Randomized RANSAC with Td,d test

Jiri Matas;Ondrej Chum

270
Citations

Frequent Co-Authors

Jiri Matas Czech Technical University in Prague

Yannis Avrithis Institute of Advanced Research on Artificial Intelligence (IARAI)

Tomas Pajdla Czech Technical University in Prague

Andrew Zisserman University of Oxford

Josef Sivic Czech Technical University in Prague

Michael Isard Google (United States)

Jan-Michael Frahm University of North Carolina at Chapel Hill

Hervé Jégou Facebook (United States)

Josef Kittler University of Surrey

Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA

External Links

Personal website of Ondrej Chum Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens up many flexible, online education options for students and professionals. For those looking to expand their business acumen, consider the most affordable online mba programs. These programs offer a cost-effective pathway to management and leadership roles in tech and beyond.

Those seeking to upskill quickly can look into one year masters programs. These intensive courses are designed to deliver advanced skills in a compressed timeframe, ideal for jump-starting a new tech career or advancing in your current role.

If speed is your priority, you might be interested in the fastest degree to get. These online programs can put you on a fast track to high-paying positions within the tech industry and related fields.

Additionally, for those specifically interested in artificial intelligence, exploring the cheapest online master's in artificial intelligence could be a smart move. Affordable options make it feasible to specialize in this growing sector without a heavy financial burden.