Παρακολούθηση
Judy Hoffman
Judy Hoffman
Assistant Professor, Georgia Tech
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα gatech.edu - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
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
59112013
Adversarial discriminative domain adaptation
E Tzeng, J Hoffman, K Saenko, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2017
51802017
Cycada: Cycle-consistent adversarial domain adaptation
J Hoffman, E Tzeng, T Park, JY Zhu, P Isola, K Saenko, AA Efros, T Darrell
ICML, 2018
31912018
Deep domain confusion: Maximizing for domain invariance
E Tzeng, J Hoffman, N Zhang, K Saenko, T Darrell
arXiv preprint arXiv:1412.3474, 2014
29342014
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
15432015
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
8362016
Visda: The visual domain adaptation challenge
X Peng, B Usman, N Kaushik, J Hoffman, D Wang, K Saenko
arXiv preprint arXiv:1710.06924, 2017
7472017
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
6032017
Cross Modal Distillation for Supervision Transfer
S Gupta, J Hoffman, J Malik
Computer Vision and Pattern Recognition (CVPR), 2016
5832016
LSDA: Large scale detection through adaptation
J Hoffman, S Guadarrama, ES Tzeng, R Hu, J Donahue, R Girshick, ...
Advances in neural information processing systems 27, 2014
3762014
Efficient learning of domain-invariant image representations
J Hoffman, E Rodner, J Donahue, T Darrell, K Saenko
International Conference on Learning Representations (ICLR), 2013
3532013
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, 2017
3242017
Predictive inequity in object detection
B Wilson, J Hoffman, J Morgenstern
arXiv preprint arXiv:1902.11097, 2019
2642019
Learning with side information through modality hallucination
J Hoffman, S Gupta, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2016
2542016
Clockwork convnets for video semantic segmentation
E Shelhamer, K Rakelly, J Hoffman, T Darrell
Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016
2502016
Algorithms and theory for multiple-source adaptation
J Hoffman, M Mohri, N Zhang
Advances in neural information processing systems 31, 2018
2442018
Discovering latent domains for multisource domain adaptation
J Hoffman, B Kulis, T Darrell, K Saenko
Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012
2242012
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
1992013
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
1872014
Best practices for fine-tuning visual classifiers to new domains
B Chu, V Madhavan, O Beijbom, J Hoffman, T Darrell
Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016
1822016
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