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
34852013
Adversarial discriminative domain adaptation
E Tzeng, J Hoffman, K Saenko, T Darrell
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
11092017
Deep domain confusion: Maximizing for domain invariance
E Tzeng, J Hoffman, N Zhang, K Saenko, T Darrell
arXiv preprint arXiv:1412.3474, 2014
6862014
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
6662015
Cycada: Cycle-consistent adversarial domain adaptation
J Hoffman, E Tzeng, T Park, JY Zhu, P Isola, K Saenko, AA Efros, T Darrell
ICML, 2018
5652018
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
2402017
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
2302014
Efficient learning of domain-invariant image representations
J Hoffman, E Rodner, J Donahue, T Darrell, K Saenko
International Conference on Learning Representations (ICLR), 2013
2302013
Cross Modal Distillation for Supervision Transfer
S Gupta, J Hoffman, J Malik
Computer Vision and Pattern Recognition (CVPR), 2016
2292016
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
2072016
Discovering latent domains for multisource domain adaptation
J Hoffman, B Kulis, T Darrell, K Saenko
European Conference on Computer Vision, 702-715, 2012
1452012
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
1142013
Learning with side information through modality hallucination
J Hoffman, S Gupta, T Darrell
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
982016
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, 165-177, 2017
922017
Clockwork convnets for video semantic segmentation
E Shelhamer, K Rakelly, J Hoffman, T Darrell
European Conference on Computer Vision, 852-868, 2016
922016
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
792014
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
732017
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
732015
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
702014
Weakly supervised learning of object segmentations from web-scale video
G Hartmann, M Grundmann, J Hoffman, D Tsai, V Kwatra, O Madani, ...
European Conference on Computer Vision, 198-208, 2012
642012
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