Kate Saenko
Cited by
Cited by
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
Adversarial discriminative domain adaptation
E Tzeng, J Hoffman, K Saenko, T Darrell
Computer Vision and Pattern Recognition (CVPR), 2017
Adapting visual category models to new domains
K Saenko, B Kulis, M Fritz, T Darrell
European conference on computer vision, 213-226, 2010
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
Deep domain confusion: Maximizing for domain invariance
E Tzeng, J Hoffman, N Zhang, K Saenko, T Darrell
arXiv preprint arXiv:1412.3474, 2014
Cycada: Cycle-consistent adversarial domain adaptation
J Hoffman, E Tzeng, T Park, JY Zhu, P Isola, K Saenko, AA Efros, T Darrell
International Conference on Machine Learning 2018, 2018
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
Translating videos to natural language using deep recurrent neural networks
S Venugopalan, H Xu, J Donahue, M Rohrbach, R Mooney, K Saenko
NAACL HLT 2015, 2014
What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
B Kulis, K Saenko, T Darrell
CVPR 2011, 1785-1792, 2011
Return of Frustratingly Easy Domain Adaptation
B Sun, J Feng, K Saenko
AAAI, 2016
Deep coral: Correlation alignment for deep domain adaptation
B Sun, K Saenko
European conference on computer vision, 443-450, 2016
Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering
H Xu, K Saenko
European Conference on Computer Vision (ECCV), 2016
A category-level 3d object dataset: Putting the kinect to work
A Janoch, S Karayev, Y Jia, JT Barron, M Fritz, K Saenko, T Darrell
Consumer Depth Cameras for Computer Vision, 141-165, 2013
Youtube2text: Recognizing and describing arbitrary activities using semantic hierarchies and zero-shot recognition
S Guadarrama, N Krishnamoorthy, G Malkarnenkar, S Venugopalan, ...
Computer Vision (ICCV), 2013 IEEE International Conference on, 2712-2719, 2013
R-C3D: Region convolutional 3d network for temporal activity detection
H Xu, A Das, K Saenko
International Conference on Computer Vision (ICCV), 2017
Natural language object retrieval
R Hu, H Xu, M Rohrbach, J Feng, K Saenko, T Darrell
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
Learning to reason: End-to-end module networks for visual question answering
R Hu, J Andreas, M Rohrbach, T Darrell, K Saenko
International Conference on Computer Vision (ICCV), 2017
Learning deep object detectors from 3d models
X Peng, B Sun, K Ali, K Saenko
Proceedings of the IEEE International Conference on Computer Vision, 1278-1286, 2015
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
Efficient learning of domain-invariant image representations
J Hoffman, E Rodner, J Donahue, T Darrell, K Saenko
International Conference in Learning Representations (ICLR), 2013
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