Judy Hoffman
Judy Hoffman
Assistant Professor, Georgia Tech
確認したメール アドレス: gatech.edu - ホームページ
タイトル
引用先
引用先
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 (ICML), 2013
40482013
Adversarial discriminative domain adaptation
E Tzeng, J Hoffman, K Saenko, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2017
17692017
Deep domain confusion: Maximizing for domain invariance
E Tzeng, J Hoffman, N Zhang, K Saenko, T Darrell
arXiv preprint arXiv:1412.3474, 2014
9742014
Cycada: Cycle-consistent adversarial domain adaptation
J Hoffman, E Tzeng, T Park, JY Zhu, P Isola, K Saenko, AA Efros, T Darrell
ICML, 2018
9522018
Simultaneous deep transfer across domains and tasks
E Tzeng, J Hoffman, T Darrell, K Saenko
Proceedings of the IEEE International Conference on Computer Vision, 4068-4076, 2015
8652015
Inferring and executing programs for visual reasoning
J Johnson, B Hariharan, L Van Der Maaten, J Hoffman, L Fei-Fei, ...
Proceedings of the IEEE International Conference on Computer Vision, 2989-2998, 2017
3072017
Fcns in the wild: Pixel-level adversarial and constraint-based adaptation
J Hoffman, D Wang, F Yu, T Darrell
arXiv preprint arXiv:1612.02649, 2016
3012016
Cross Modal Distillation for Supervision Transfer
S Gupta, J Hoffman, J Malik
Computer Vision and Pattern Recognition (CVPR), 2016
2842016
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
2702014
Efficient learning of domain-invariant image representations
J Hoffman, E Rodner, J Donahue, T Darrell, K Saenko
International Conference on Learning Representations (ICLR), 2013
2692013
Discovering latent domains for multisource domain adaptation
J Hoffman, B Kulis, T Darrell, K Saenko
European Conference on Computer Vision, 702-715, 2012
1722012
Label efficient learning of transferable representations acrosss domains and tasks
Z Luo, Y Zou, J Hoffman, LF Fei-Fei
Advances in neural information processing systems 30, 165-177, 2017
1432017
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
1382013
Learning with side information through modality hallucination
J Hoffman, S Gupta, T Darrell
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
1342016
Clockwork convnets for video semantic segmentation
E Shelhamer, K Rakelly, J Hoffman, T Darrell
European Conference on Computer Vision, 852-868, 2016
1122016
Visda: The visual domain adaptation challenge
X Peng, B Usman, N Kaushik, J Hoffman, D Wang, K Saenko
arXiv preprint arXiv:1710.06924, 2017
1002017
Fine-grained recognition in the wild: A multi-task domain adaptation approach
T Gebru, J Hoffman, L Fei-Fei
Proceedings of the IEEE International Conference on Computer Vision, 1349-1358, 2017
992017
Continuous manifold based adaptation for evolving visual domains
J Hoffman, T Darrell, K Saenko
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014
952014
Towards adapting deep visuomotor representations from simulated to real environments
E Tzeng, C Devin, J Hoffman, C Finn, X Peng, S Levine, K Saenko, ...
arXiv preprint arXiv:1511.07111 2 (3), 2015
802015
Best practices for fine-tuning visual classifiers to new domains
B Chu, V Madhavan, O Beijbom, J Hoffman, T Darrell
European conference on computer vision, 435-442, 2016
772016
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