| Fully convolutional networks for semantic segmentation J Long, E Shelhamer, T Darrell Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 47511 | 2015 |
| 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 | 41832 | 2014 |
| 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 | 18575 | 2014 |
| Fully convolutional networks for semantic segmentation E Shelhamer, J Long, T Darrell IEEE transactions on pattern analysis and machine intelligence 39 (4), 640-651, 2016 | 8878 | 2016 |
| 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 | 8216 | 2015 |
| 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 | 7495 | 2022 |
| 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 | 7101 | 1997 |
| 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 | 7002 | 2016 |
| 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 | 6237 | 2014 |
| Adversarial discriminative domain adaptation E Tzeng, J Hoffman, K Saenko, T Darrell Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 6016 | 2017 |
| 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 | 4319 | 2016 |
| 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 | 3709 | 2018 |
| Adapting visual category models to new domains K Saenko, B Kulis, M Fritz, T Darrell Computer vision–ECCV 2010: 11th European conference on computer vision …, 2010 | 3603 | 2010 |
| 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 | 3556 | 2015 |
| Deep domain confusion: Maximizing for domain invariance E Tzeng, J Hoffman, N Zhang, K Saenko, T Darrell arXiv preprint arXiv:1412.3474, 2014 | 3422 | 2014 |
| Curiosity-driven exploration by self-supervised prediction D Pathak, P Agrawal, AA Efros, T Darrell International conference on machine learning, 2778-2787, 2017 | 3115 | 2017 |
| 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 | 2683 | 2020 |
| Adversarial feature learning J Donahue, P Krähenbühl, T Darrell arXiv preprint arXiv:1605.09782, 2016 | 2637 | 2016 |
| 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 | 2219 | 2005 |
| Toward multimodal image-to-image translation JY Zhu, R Zhang, D Pathak, T Darrell, AA Efros, O Wang, E Shechtman Advances in neural information processing systems 30, 2017 | 1998 | 2017 |
Kate SaenkoBoston UniversityVerified email at bu.edu
