Trevor J. Darrell
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Media Technology top 0.01%
Papers in
-
- Advanced Image and Video Retrieval Techniques 122
- Multimodal Machine Learning Applications 114
- Human Pose and Action Recognition 65
- Advanced Vision and Imaging 61
- Advanced Neural Network Applications 56
- Video Surveillance and Tracking Methods 47
-
- Domain Adaptation and Few-Shot Learning 116
- Co-authors
- Evan Shelhamer (13 shared papers)Jonathan Long (4 shared papers)Jeff Donahue (11 shared papers)Ross Girshick (12 shared papers)Jitendra Malik (10 shared papers)Kate Saenko (53 shared papers)Sergio Guadarrama (9 shared papers)Marcus Rohrbach (22 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (15 papers)International Journal of Computer Vision (5 papers)Lecture notes in computer science (41 papers)Computer Vision and Image Understanding (3 papers)Advances in computer vision and pattern recognition (2 papers)
- Partner nations
- United StatesGermanyIsrael
In The Last Decade
Trevor J. Darrell
443 papers receiving 124.1k citations
Trevor J. Darrell's Hit Papers
Peers
Comparison fields: 5 of 225
- Computer Vision and Pattern Recognition 86.1k
- Media Technology 12.5k
- Artificial Intelligence 40.4k
- Human-Computer Interaction 4.2k
- Industrial and Manufacturing Engineering 5.4k
Countries citing papers authored by Trevor J. Darrell
This map shows the geographic impact of Trevor J. Darrell'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 Trevor J. Darrell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Trevor J. Darrell more than expected).
Fields of papers citing papers by Trevor J. Darrell
This network shows the impact of papers produced by Trevor J. Darrell. 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 Trevor J. Darrell. The network helps show where Trevor J. Darrell may publish in the future.
Co-authors
The 25 scholars most cited alongside Trevor J. Darrell, 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 461 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Fully convolutional networks for semantic segmentation Hit paper breakdown → | 2015 | 27688 |
| 2 | Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation Hit paper breakdown → | 2014 | 23827 |
| 3 | Caffe Hit paper breakdown → | 2014 | 9272 |
| 4 | Fully Convolutional Networks for Semantic Segmentation Hit paper breakdown → | 2016 | 9180 |
| 5 | A ConvNet for the 2020s Hit paper breakdown → | 2022 | 5058 |
| 6 | Long-term recurrent convolutional networks for visual recognition and description Hit paper breakdown → | 2015 | 3751 |
| 7 | Adversarial Discriminative Domain Adaptation Hit paper breakdown → | 2017 | 3597 |
| 8 | Pfinder: real-time tracking of the human body Hit paper breakdown → | 1997 | 3322 |
| 9 | Region-Based Convolutional Networks for Accurate Object Detection and Segmentation Hit paper breakdown → | 2015 | 2279 |
| 10 | Adapting Visual Category Models to New Domains Hit paper breakdown → | 2010 | 1975 |
| 11 | BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning Hit paper breakdown → | 2020 | 1728 |
| 12 | Long-Term Recurrent Convolutional Networks for Visual Recognition and Description Hit paper breakdown → | 2016 | 1221 |
| 13 | The pyramid match kernel: discriminative classification with sets of image features Hit paper breakdown → | 2005 | 1160 |
| 14 | Deep Layer Aggregation Hit paper breakdown → | 2018 | 1143 |
| 15 | Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding Hit paper breakdown → | 2016 | 1066 |
| 16 | Sequence to Sequence -- Video to Text Hit paper breakdown → | 2015 | 1025 |
| 17 | Part-Based R-CNNs for Fine-Grained Category Detection Hit paper breakdown → | 2014 | 916 |
| 18 | Simultaneous Deep Transfer Across Domains and Tasks Hit paper breakdown → | 2015 | 892 |
| 19 | End-to-end training of deep visuomotor policies Hit paper breakdown → | 2016 | 875 |
| 20 | Compact Bilinear Pooling Hit paper breakdown → | 2016 | 641 |
About Trevor J. Darrell
Trevor J. Darrell is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Signal Processing and Aerospace Engineering, having authored 461 papers that have together received 128.4k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (122 papers), Domain Adaptation and Few-Shot Learning (116 papers), Multimodal Machine Learning Applications (114 papers), Human Pose and Action Recognition (65 papers), Advanced Vision and Imaging (61 papers), Advanced Neural Network Applications (56 papers), Video Surveillance and Tracking Methods (47 papers) and Robotics and Sensor-Based Localization (37 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (86.1k citations), Media Technology (12.5k citations), Artificial Intelligence (40.4k citations), Human-Computer Interaction (4.2k citations) and Industrial and Manufacturing Engineering (5.4k citations). Trevor J. Darrell has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Evan Shelhamer, Jonathan Long, Jeff Donahue, Ross Girshick, Jitendra Malik, Kate Saenko, Sergio Guadarrama, Marcus Rohrbach, Yangqing Jia and Judy Hoffman. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, Lecture notes in computer science, Computer Vision and Image Understanding and Advances in computer vision and pattern recognition.
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.