Jeff Donahue
Jeff Donahue
Research Scientist, DeepMind
Vahvistettu sähköpostiosoite verkkotunnuksessa google.com - Kotisivu
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Viittaukset
Viittaukset
Vuosi
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
148342014
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
140972014
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
42522015
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
39582014
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
21472016
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
13982015
Large scale GAN training for high fidelity natural image synthesis
A Brock, J Donahue, K Simonyan
arXiv preprint arXiv:1809.11096, 2018
12002018
Adversarial feature learning
J Donahue, P Krähenbühl, T Darrell
arXiv preprint arXiv:1605.09782, 2016
9702016
Sequence to sequence-video to text
S Venugopalan, M Rohrbach, J Donahue, R Mooney, T Darrell, K Saenko
Proceedings of the IEEE international conference on computer vision, 4534-4542, 2015
9542015
Part-based R-CNNs for fine-grained category detection
N Zhang, J Donahue, R Girshick, T Darrell
European conference on computer vision, 834-849, 2014
8062014
Translating videos to natural language using deep recurrent neural networks
S Venugopalan, H Xu, J Donahue, M Rohrbach, R Mooney, K Saenko
arXiv preprint arXiv:1412.4729, 2014
7402014
Generating visual explanations
LA Hendricks, Z Akata, M Rohrbach, J Donahue, B Schiele, T Darrell
European Conference on Computer Vision, 3-19, 2016
3272016
LSDA: Large scale detection through adaptation
J Hoffman, S Guadarrama, ES Tzeng, R Hu, J Donahue, R Girshick, ...
Advances in Neural Information Processing Systems, 3536-3544, 2014
2652014
Population based training of neural networks
M Jaderberg, V Dalibard, S Osindero, WM Czarnecki, J Donahue, ...
arXiv preprint arXiv:1711.09846, 2017
2582017
Efficient learning of domain-invariant image representations
J Hoffman, E Rodner, J Donahue, T Darrell, K Saenko
arXiv preprint arXiv:1301.3224, 2013
2582013
Data-dependent initializations of convolutional neural networks
P Krähenbühl, C Doersch, J Donahue, T Darrell
arXiv preprint arXiv:1511.06856, 2015
1482015
Semi-supervised domain adaptation with instance constraints
J Donahue, J Hoffman, E Rodner, K Saenko, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2013
1332013
Large scale adversarial representation learning
J Donahue, K Simonyan
Advances in Neural Information Processing Systems, 10542-10552, 2019
1032019
Visual search at pinterest
Y Jing, D Liu, D Kislyuk, A Zhai, J Xu, J Donahue, S Tavel
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
1022015
Asymmetric and category invariant feature transformations for domain adaptation
J Hoffman, E Rodner, J Donahue, B Kulis, K Saenko
International journal of computer vision 109 (1-2), 28-41, 2014
762014
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Artikkelit 1–20