Trevor Darrell

202.1k citations

389 papers · 78.9k indexed · 27 hit papers · h-index 84

Computer Vision and Pattern Recognition top 0.01%
- Advanced Image and Video Retrieval Techniques 103
- Multimodal Machine Learning Applications 81
- Human Pose and Action Recognition 56
- Advanced Vision and Imaging 56
- Advanced Neural Network Applications 44
- Video Surveillance and Tracking Methods 43
- Image Retrieval and Classification Techniques 34
Media Technology top 0.01%
Artificial Intelligence top 0.01%
- Domain Adaptation and Few-Shot Learning 93
Human-Computer Interaction top 0.02%
Industrial and Manufacturing Engineering top 0.02%

Co-authors: Jeff Donahue Ross Girshick Jitendra Malik Evan Shelhamer Jonathan Long Kate Saenko Sergio Guadarrama Yangqing Jia
Cited by: Computer Vision and Pattern Recognition Media Technology Artificial Intelligence
Journals: IEEE Transactions on Pattern Analysis and Machine Intelligence (17 papers)International Journal of Computer Vision (5 papers)Computer Vision and Image Understanding (4 papers)
Partner nations: United States Germany Israel

In The Last Decade

Trevor Darrell

377 papers receiving 75.4k citations

Hit Papers

15 papers align trajectories log scale

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

2023 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
2022 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2022 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2021 Quasi-Dense Similarity Learning for Multiple Object Tracking
2021 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
2020 BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
2019 Few-Shot Object Detection via Feature Reweighting
2019 Semi-Supervised Domain Adaptation via Minimax Entropy
2018 Deep Layer Aggregation
2017 Adversarial Discriminative Domain Adaptation
2016 Journal of Machine Learning Research
2016 IEEE Transactions on Pattern Analysis and Machine Intelligence
2016 IEEE Transactions on Pattern Analysis and Machine Intelligence
2015 Long-term recurrent convolutional networks for visual recognition and description
2015 Simultaneous Deep Transfer Across Domains and Tasks
2015 Sequence to Sequence -- Video to Text
2015 IEEE Transactions on Pattern Analysis and Machine Intelligence
2015 Constrained Convolutional Neural Networks for Weakly Supervised Segmentation
2014 Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
2014 Caffe
2014 PANDA: Pose Aligned Networks for Deep Attribute Modeling
2013 arXiv (Cornell University)
2013 YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-Shot Recognition
2011 What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
2009 UC Berkeley
2005 The pyramid match kernel: discriminative classification with sets of image features
1997 IEEE Transactions on Pattern Analysis and Machine Intelligence

Peers

Countries citing papers authored by Trevor Darrell

Since Specialization

Citations

This map shows the geographic impact of Trevor 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 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 Darrell more than expected).

Fields of papers citing papers by Trevor Darrell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Trevor 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 Darrell. The network helps show where Trevor Darrell may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Trevor Darrell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Trevor Darrell Line = papers co-authored together Trevor Darrell links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	Aligning Large Multimodal Models with Factually Augmented RLHF Zhiqing Sun,Sheng Shen,Beo Oliveira Leite,W. G. HOSKINS,Chunyuan Li,Yikang Shen,Chuang Gan,Liang-Yan Gui,Yu-Xiong Wang,Yiming Yang,Kurt Keutzer,Trevor Darrell	2024	29
2	ALOHa: A New Measure for Hallucination in Captioning Models Semenov-Tian-Shansky,David W. Chan,I Made Dwi Wira Ardana,Canales Pérez,John Canny,Joseph E. Gonzalez,Trevor Darrell	2024	2
3	Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs Roei Herzig,K. Kuefner,Leonid Karlinsky,Assaf Arbelle,Rogério Feris,Trevor Darrell,Amir Globerson	2023	6
4	QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking IEEE Transactions on Pattern Analysis and Machine Intelligence ·Jia-Yi Zhan,T. Huang,Jiangmiao Pang,Linlu Qiu,Haofeng Chen,Trevor Darrell,Fisher Yu	2023	63
5	Towards Learning to Play Piano with Dexterous Hands and Touch 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ·Huazhe Xu,Yuping Luo,Shaoxiong Wang,Trevor Darrell,Roberto Calandra	2022	20
6	Monocular Quasi-Dense 3D Object Tracking IEEE Transactions on Pattern Analysis and Machine Intelligence ·Hou-Ning Hu,LUIGI MONGA,Jia-Yi Zhan,Trevor Darrell,Fisher Yu,Min Sun	2022	84
7	Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learningbreakdown → 2021 IEEE/CVF International Conference on Computer Vision (ICCV) ·Yinbo Chen,Zhuang Liu,Huijuan Xu,Trevor Darrell,Xiaolong Wang	2021	265
8	Quasi-Dense Similarity Learning for Multiple Object Trackingbreakdown → Jiangmiao Pang,Linlu Qiu,Xia Li,Haofeng Chen,Qi Li,Trevor Darrell,Fisher Yu	2021	268
9	Early Convolutions Help Transformers See Better Neural Information Processing Systems ·Tete Xiao,Mannat Singh,M. Castagnini,Trevor Darrell,Piotr Dollár,Ross Girshick	2021	2
10	Joint Monocular 3D Vehicle Detection and Tracking Hou-Ning Hu,Qi-Zhi Cai,Dequan Wang,Ji Lin,Min Sun,N. A. Bel'kova,Trevor Darrell,Fisher Yu	2019	154
11	Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended Abstract. Computer Vision and Pattern Recognition ·Sayna Ebrahimi,Mohamed Elhoseiny,Trevor Darrell,Marcus Rohrbach	2019	2
12	Localizing Moments in Video with Natural Language arXiv (Cornell University) ·Lisa Anne Hendricks,Oliver Wang,Eli Shechtman,Josef Šivic,Trevor Darrell,Bryan Russell	2017	39
13	Can you fool AI with adversarial examples on a visual Turing test arXiv (Cornell University) ·Xiaojun Xu,Xinyun Chen,Chang Liu,Anna Rohrbach,Trevor Darrell,Dawn Song	2017	13
14	Learning to Compose Neural Networks for Question Answering Jacob Andreas,Marcus Rohrbach,Trevor Darrell,Dan Klein	2016	234
15	Deformable part models are convolutional neural networks Ross Girshick,Forrest Iandola,Trevor Darrell,Jitendra Malik	2015	253
16	Continuous Manifold Based Adaptation for Evolving Visual Domains Judy Hoffman,Trevor Darrell,Kate Saenko	2014	74
17	One-Bit Object Detection: On learning to localize objects with minimal supervision. arXiv (Cornell University) ·Hyun Oh Song,Ross Girshick,Stefanie Jegelka,Julien Mairal,Zaïd Harchaoui,Trevor Darrell	2014	4
18	One-Shot Adaptation of Supervised Deep Convolutional Models arXiv (Cornell University) ·Judy Hoffman,Eric Tzeng,Jeff Donahue,Yangqing Jia,Kate Saenko,Trevor Darrell	2013	10
19	Timely Object Recognition MPG.PuRe (Max Planck Society) ·Sergey Karayev,右近修治,Mario Fritz,Trevor Darrell	2012	25
20	Factorized Orthogonal Latent Spaces Bristol Research (University of Bristol) ·Mathieu Salzmann,Carl Henrik Ek,Raquel Urtasun,Trevor Darrell	2010	52

About Trevor Darrell

Trevor Darrell is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 389 papers that have together received 78.9k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (103 papers), Domain Adaptation and Few-Shot Learning (93 papers), Multimodal Machine Learning Applications (81 papers), Human Pose and Action Recognition (56 papers), Advanced Vision and Imaging (56 papers), Advanced Neural Network Applications (44 papers), Video Surveillance and Tracking Methods (43 papers) and Image Retrieval and Classification Techniques (34 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (54.3k citations), Media Technology (7.5k citations) and Artificial Intelligence (24.0k citations). Trevor Darrell has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Jeff Donahue, Ross Girshick, Jitendra Malik, Evan Shelhamer, Jonathan Long, Kate Saenko, Sergio Guadarrama, Yangqing Jia, Judy Hoffman and Eric Tzeng. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, Computer Vision and Image Understanding, Communications of the ACM and The International Journal of Robotics Research.

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.

Explore authors with similar magnitude of impact