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Trevor Darrell
Trevor Darrell
Professor of Computer Science, U.C. Berkeley
Verified email at eecs.berkeley.edu - Homepage
Title
Cited by
Cited by
Year
Fully convolutional networks for semantic segmentation
J Long, E Shelhamer, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2015
616672015
Rich feature hierarchies for accurate object detection and semantic segmentation
R Girshick, J Donahue, T Darrell, J Malik
Proceedings of the IEEE conference on computer vision and pattern …, 2014
463052014
Caffe: Convolutional architecture for fast feature embedding
Y Jia, E Shelhamer, J Donahue, S Karayev, J Long, R Girshick, ...
Proceedings of the 22nd ACM international conference on Multimedia, 675-678, 2014
185862014
A convnet for the 2020s
Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
126222022
Long-term recurrent convolutional networks for visual recognition and description
J Donahue, L Anne Hendricks, S Guadarrama, M Rohrbach, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2015
86852015
Context encoders: Feature learning by inpainting
D Pathak, P Krahenbuhl, J Donahue, T Darrell, AA Efros
Proceedings of the IEEE conference on computer vision and pattern …, 2016
77702016
Pfinder: Real-time tracking of the human body
CR Wren, A Azarbayejani, T Darrell, AP Pentland
IEEE Transactions on pattern analysis and machine intelligence 19 (7), 780-785, 1997
69971997
Adversarial discriminative domain adaptation
E Tzeng, J Hoffman, K Saenko, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2017
69362017
Decaf: A deep convolutional activation feature for generic visual recognition
J Donahue, Y Jia, O Vinyals, J Hoffman, N Zhang, E Tzeng, T Darrell
International conference on machine learning, 647-655, 2014
63932014
End-to-end training of deep visuomotor policies
S Levine, C Finn, T Darrell, P Abbeel
Journal of Machine Learning Research 17 (39), 1-40, 2016
49712016
Cycada: Cycle-consistent adversarial domain adaptation
J Hoffman, E Tzeng, T Park, JY Zhu, P Isola, K Saenko, A Efros, T Darrell
International conference on machine learning, 1989-1998, 2018
41142018
Region-based convolutional networks for accurate object detection and segmentation
R Girshick, J Donahue, T Darrell, J Malik
IEEE transactions on pattern analysis and machine intelligence 38 (1), 142-158, 2015
39932015
Adapting visual category models to new domains
K Saenko, B Kulis, M Fritz, T Darrell
European conference on computer vision, 213-226, 2010
39562010
Deep domain confusion: Maximizing for domain invariance
E Tzeng, J Hoffman, N Zhang, K Saenko, T Darrell
arXiv preprint arXiv:1412.3474, 2014
38672014
Curiosity-driven exploration by self-supervised prediction
D Pathak, P Agrawal, AA Efros, T Darrell
International conference on machine learning, 2778-2787, 2017
38272017
Bdd100k: A diverse driving dataset for heterogeneous multitask learning
F Yu, H Chen, X Wang, W Xian, Y Chen, F Liu, V Madhavan, T Darrell
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
37992020
Adversarial feature learning
J Donahue, P Krähenbühl, T Darrell
arXiv preprint arXiv:1605.09782, 2016
28142016
Rethinking the value of network pruning
Z Liu, M Sun, T Zhou, G Huang, T Darrell
arXiv preprint arXiv:1810.05270, 2018
22502018
Tent: Fully test-time adaptation by entropy minimization
D Wang, E Shelhamer, S Liu, B Olshausen, T Darrell
arXiv preprint arXiv:2006.10726, 2020
21862020
The pyramid match kernel: Discriminative classification with sets of image features
K Grauman, T Darrell
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 2 …, 2005
21772005
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Articles 1–20