Andrew Zisserman
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Image Retrieval and Classification Techniques
- Human Pose and Action Recognition
- Media Technology top 0.01%
Papers in
-
- Advanced Image and Video Retrieval Techniques 177
- Advanced Vision and Imaging 140
- Image Retrieval and Classification Techniques 90
- Human Pose and Action Recognition 80
- Video Surveillance and Tracking Methods 58
- Multimodal Machine Learning Applications 55
-
- Domain Adaptation and Few-Shot Learning 50
- Co-authors
- Karen Simonyan (12 shared papers)Richard Hartley (24 shared papers)Luc Van Gool (12 shared papers)Mark Everingham (17 shared papers)Christopher K. I. Williams (6 shared papers)Andrea Vedaldi (40 shared papers)John Winn (5 shared papers)Josef Šivic (31 shared papers)
- Journals
- International Journal of Computer Vision (29 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (20 papers)Image and Vision Computing (18 papers)Lecture notes in computer science (123 papers)Computer Vision and Image Understanding (5 papers)
- Partner nations
- United KingdomUnited StatesFrance
In The Last Decade
Andrew Zisserman
568 papers receiving 157.2k citations
Andrew Zisserman's Hit Papers
Peers
Comparison fields: 5 of 236
- Computer Vision and Pattern Recognition 122.1k
- Media Technology 17.5k
- Artificial Intelligence 39.4k
- Signal Processing 12.1k
- Aerospace Engineering 23.6k
Countries citing papers authored by Andrew Zisserman
This map shows the geographic impact of Andrew Zisserman'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 Andrew Zisserman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Zisserman more than expected).
Fields of papers citing papers by Andrew Zisserman
This network shows the impact of papers produced by Andrew Zisserman. 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 Andrew Zisserman. The network helps show where Andrew Zisserman may publish in the future.
Co-authors
The 25 scholars most cited alongside Andrew Zisserman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 587 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Very Deep Convolutional Networks for Large-Scale Image Recognition Hit paper breakdown → | 2014 | 54851 |
| 2 | Multiple View Geometry in Computer Vision Hit paper breakdown → | 2004 | 15605 |
| 3 | The Pascal Visual Object Classes (VOC) Challenge Hit paper breakdown → | 2009 | 13716 |
| 4 | The Pascal Visual Object Classes Challenge: A Retrospective Hit paper breakdown → | 2014 | 4932 |
| 5 | Deep Face Recognition Hit paper breakdown → | 2015 | 3464 |
| 6 | Multiple View Geometry in Computer Vision (2nd ed) Hit paper breakdown → | 2003 | 2359 |
| 7 | A Comparison of Affine Region Detectors Hit paper breakdown → | 2005 | 2294 |
| 8 | Object retrieval with large vocabularies and fast spatial matching Hit paper breakdown → | 2007 | 2200 |
| 9 | Convolutional Two-Stream Network Fusion for Video Action Recognition Hit paper breakdown → | 2016 | 2001 |
| 10 | VGGFace2: A Dataset for Recognising Faces across Pose and Age Hit paper breakdown → | 2018 | 1829 |
| 11 | The PASCAL visual object classes challenge 2006 (VOC2006) results Hit paper breakdown → | 2006 | 1816 |
| 12 | Object class recognition by unsupervised scale-invariant learning Hit paper breakdown → | 2003 | 1591 |
| 13 | VoxCeleb2: Deep Speaker Recognition Hit paper breakdown → | 2018 | 1401 |
| 14 | Visual Reconstruction Hit paper breakdown → | 1987 | 1366 |
| 15 | Non-local sparse models for image restoration Hit paper breakdown → | 2009 | 1295 |
| 16 | Representing shape with a spatial pyramid kernel Hit paper breakdown → | 2007 | 1119 |
| 17 | Lost in quantization: Improving particular object retrieval in large scale image databases Hit paper breakdown → | 2008 | 1077 |
| 18 | Synthetic Data for Text Localisation in Natural Images Hit paper breakdown → | 2016 | 1021 |
| 19 | Image Classification using Random Forests and Ferns Hit paper breakdown → | 2007 | 1009 |
| 20 | Three things everyone should know to improve object retrieval Hit paper breakdown → | 2012 | 987 |
About Andrew Zisserman
Andrew Zisserman is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Media Technology and Signal Processing, having authored 587 papers that have together received 164.6k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (177 papers), Advanced Vision and Imaging (140 papers), Image Retrieval and Classification Techniques (90 papers), Human Pose and Action Recognition (80 papers), Robotics and Sensor-Based Localization (60 papers), Video Surveillance and Tracking Methods (58 papers), Multimodal Machine Learning Applications (55 papers) and Domain Adaptation and Few-Shot Learning (50 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (122.1k citations), Media Technology (17.5k citations), Artificial Intelligence (39.4k citations), Signal Processing (12.1k citations) and Aerospace Engineering (23.6k citations). Andrew Zisserman has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Karen Simonyan, Richard Hartley, Luc Van Gool, Mark Everingham, Christopher K. I. Williams, Andrea Vedaldi, John Winn, Josef Šivic, Omkar Parkhi and Manik Varma. Their work appears in journals such as International Journal of Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, Image and Vision Computing, Lecture notes in computer science and Computer Vision and Image Understanding.
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.