Philip Torr
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Advanced Vision and Imaging
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- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Natural Language Processing Techniques
Papers in
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- Advanced Image and Video Retrieval Techniques 3
- Multimodal Machine Learning Applications 3
- Advanced Vision and Imaging 2
- Visual Attention and Saliency Detection 2
- Augmented Reality Applications 1
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- Speech and dialogue systems 3
- Natural Language Processing Techniques 3
- Topic Modeling 2
- Co-authors
- Hengshuang Zhao (2 shared papers)Zhao Yang (1 shared paper)Jiaqi Wang (1 shared paper)Kai Chen (1 shared paper)Yansong Tang (1 shared paper)Chris Russell (1 shared paper)Ľubor Ladický (1 shared paper)Sunando Sengupta (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (2 papers)Pattern Recognition (1 paper)Research at the University of Copenhagen (University of Copenhagen) (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)Oxford University Research Archive (ORA) (University of Oxford) (3 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Philip Torr
8 papers receiving 237 citations
Philip Torr's Hit Papers
Peers
Comparison fields: 5 of 47
- Computer Vision and Pattern Recognition 186
- Artificial Intelligence 80
- Media Technology 19
- Computational Mathematics 1
- Neurology 7
Countries citing papers authored by Philip Torr
This map shows the geographic impact of Philip Torr'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 Philip Torr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip Torr more than expected).
Fields of papers citing papers by Philip Torr
This network shows the impact of papers produced by Philip Torr. 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 Philip Torr. The network helps show where Philip Torr may publish in the future.
Co-authors
The 25 scholars most cited alongside Philip Torr, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | LAVT: Language-Aware Vision Transformer for Referring Image Segmentation Hit paper breakdown → | 2022 | 184 |
| 2 | 2010 | 33 | |
| 3 | 2022 | 6 | |
| 4 | 2023 | 5 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 3 | |
| 7 | 2025 | 2 | |
| 8 | 2025 | 1 | |
| 9 | 2025 | 0 | |
| 10 | 2025 | 0 | |
| 11 | 2025 | 0 | |
| 12 | 2025 | 0 | |
| 13 | 2025 | 0 | |
| 14 | 2025 | 0 |
About Philip Torr
Philip Torr is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Computer Networks and Communications and Numerical Analysis, having authored 14 papers that have together received 239 indexed citations. Recurring topics across this work include Speech and dialogue systems (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Natural Language Processing Techniques (3 papers), Multimodal Machine Learning Applications (3 papers), Advanced Vision and Imaging (2 papers), Topic Modeling (2 papers), Visual Attention and Saliency Detection (2 papers) and Augmented Reality Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (186 citations), Artificial Intelligence (80 citations), Media Technology (19 citations), Computational Mathematics (1 citation) and Neurology (7 citations). Philip Torr has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Hengshuang Zhao, Zhao Yang, Jiaqi Wang, Kai Chen, Yansong Tang, Chris Russell, Ľubor Ladický, Sunando Sengupta, William F. Clocksin and Yalın Baştanlar. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition, Research at the University of Copenhagen (University of Copenhagen), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Oxford University Research Archive (ORA) (University of Oxford).
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.