Publications
For the most up to date list, see this Google Scholar page.
2016
Huijuan Xu, Kate Saenko. "Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering". In European Conference on Computer Vision (ECCV), 2016.
Xingchao Peng, Kate Saenko, Combining Texture and Shape Cues for Object Detection with Minimal Supervision, ACCV 2016.
Xingchao Peng, Judy Hoffman, Stella X Yu, Kate Saenko, Fine-to-coarse Knowledge Transfer For Low-Res Image Classification, ICIP 2016.
Baochen Sun and Kate Saenko, Deep CORAL: Correlation Alignment for Deep Domain Adaptation(Extended Abstract), arXiv 2016.
Ronghang Hu, Huazhe Xu, Marcus Rohrbach, Jiashi Feng, Kate Saenko, Trevor Darrell, Natural Language Object Retrieval, CVPR Oral Presentation, 2016.
Lisa Anne Hendricks, Subhashini Venugopalan, Marcus Rohrbach, Raymond Mooney, Kate Saenko, Trevor Darrell, Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data, CVPR Oral Presentation, 2016.
Baochen Sun, Jiashi Feng, Kate Saenko; Return of Frustratingly Easy Domain Adaptation; AAAI, 2016.
2015
Huijuan Xu and Kate Saenko, Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering, arXiv 2015.
Baochen Sun, Jiashi Feng, Kate Saenko; Return of Frustratingly Easy Domain Adaptation (Extended Abstract); Best Paper Prize of TASK-CV Workshop at ICCV, 2015.
D. Mrowca, M. Rohrbach, J. Hoffman, R. Hu, K. Saenko, T. Darrell, Spatial Semantic Regularisation for Large Scale Object Detection, Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2015.
S. Venugopalan, M. Rohrbach, J. Donahue, R. Mooney, T. Darrell, K. Saenko, Sequence to sequence-video to text , Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2015.
Xingchao Peng, Baochen Sun, Karim Ali, Kate Saenko, Learning Deep Object Detectors from 3D Models; ICCV, 2015.
E. Tzeng, J. Hoffman, T. Darrell, K. Saenko, Simultaneous Deep Transfer Across Domains and Tasks ICCV, 2015.
Baochen Sun, Kate Saenko; Subspace Distribution Alignment for Unsupervised Domain Adaptation; BMVC, 2015.
Baochen Sun, Xingchao Peng, Kate Saenko; Generating Large Scale Image Datasets from 3D CAD Models; The Future of Datasets in Vision Workshop at CVPR, 2015.
Huijuan Xu, Subhashini Venugopalan, Vasili Ramanishka, Marcus Rohrbach, Kate Saenko; A Multi-scale Multiple Instance Video Description Network; arXiv 2015.
Jeff Donahue, Lisa Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, Trevor Darrell. Long-term Recurrent Convolutional Networks for Visual Recognition and Description. CVPR 2015. [Project Website & Code]
Subhashini Venugopalan, Huijun Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney, Kate Saenko. Translating Videos to Natural Language Using Deep Recurrent Neural Networks. NAACL 2015.
Hoffman, Judy; Pathak, Deepak; Darrell, Trevor; Saenko, Kate; Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning, CVPR, 2015
Peng, Xingchao; Sun, Baochen; Ali, Karim; Saenko, Kate; Exploring Invariances in Deep Convolutional Neural Networks Using Synthetic Images, ICLR, Workshop Track, 2014
2014
Donahue, Jeff; Hendricks, Lisa Anne; Guadarrama, Sergio; Rohrbach, Marcus; Venugopalan, Subhashini; Saenko, Kate; Darrell, Trevor; Long-term recurrent convolutional networks for visual recognition and description, arXiv preprint arXiv:1411.4389, 2014
Hoffman, Judy; Pathak, Deepak; Darrell, Trevor; Saenko, Kate; Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning, arXiv preprint arXiv:1412.1135, 2014
Tzeng, Eric; Hoffman, Judy; Zhang, Ning; Saenko, Kate; Darrell, Trevor; Deep Domain Confusion: Maximizing for Domain Invariance, arXiv preprint arXiv:1412.3474, 2014
Venugopalan, Subhashini; Xu, Huijuan; Donahue, Jeff; Rohrbach, Marcus; Mooney, Raymond; Saenko, Kate; Translating Videos to Natural Language Using Deep Recurrent Neural Networks, arXiv preprint arXiv:1412.4729, 2014
Peng, Xingchao; Sun, Baochen; Ali, Karim; Saenko, Kate; Exploring Invariances in Deep Convolutional Neural Networks Using Synthetic Images, arXiv preprint arXiv:1412.7122, 2014
Chakrabarti, Ayan; Xiong, Ying; Sun, Baochen; Darrell, Trevor; Scharstein, Daniel; Zickler, Todd; Saenko, Kate; Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images , IEEE, 2014
Goehring, Daniel; Hoffman, Judy; Rodner, Erik; Saenko, Kate; Darrell, Trevor; Interactive adaptation of real-time object detectors , Robotics and Automation (ICRA), 2014 IEEE International Conference on, IEEE, 2014
Hoffman, Judy; Rodner, Erik; Donahue, Jeff; Kulis, Brian; Saenko, Kate; Asymmetric and Category Invariant Feature Transformations for Domain Adaptation, International Journal of Computer Vision, Springer US, 2014
Sun, Baochen; Saenko, Kate; From virtual to reality: Fast adaptation of virtual object detectors to real domains , BMVC, 2014
Ali, Karim; Saenko, Kate; Confidence-rated multiple instance boosting for object detection , Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, IEEE, 2014
Guadarrama, Sergio; Rodner, Erik; Saenko, Kate; Zhang, Ning; Farrell, Ryan; Donahue, Jeff; Darrell, Trevor; Open-vocabulary object retrieval ,RSS, 2014
J. Thomason, S. Venugopalan, S. Guadarrama, K. Saenko, and R. Mooney. Integrating language and vision to generate natural language descriptions of videos in the wild. In Proceedings of the 25th International Conference on Computational Linguistics (COLING), August 2014.
Hoffman, Judy; Darrell, Trevor; Saenko, Kate; Continuous manifold based adaptation for evolving visual domains , Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, IEEE, 2014
Hoffman, Judy; Guadarrama, Sergio; Tzeng, Eric S; Hu, Ronghang; Donahue, Jeff; Girshick, Ross; Darrell, Trevor; Saenko, Kate; LSDA: Large scale detection through adaptation, Advances in Neural Information Processing Systems, 2014
2013
Hoffman, Judy; Rodner, Erik; Donahue, Jeff; Darrell, Trevor; Saenko, Kate; Efficient learning of domain-invariant image representations, arXiv preprint arXiv:1301.3224, 2013
Rodner, Erik; Hoffman, Judy; Donahue, Jeff; Darrell, Trevor; Saenko, Kate; Towards adapting imagenet to reality: Scalable domain adaptation with implicit low-rank transformations, arXiv preprint arXiv:1308.4200, 2013
Hoffman, Judy; Tzeng, Eric; Donahue, Jeff; Jia, Yangqing; Saenko, Kate; Darrell, Trevor; One-Shot Adaptation of Supervised Deep Convolutional Models, arXiv preprint arXiv:1312.6204, 2013
Janoch, Allison; Karayev, Sergey; Jia, Yangqing; Barron, Jonathan T; Fritz, Mario; Saenko, Kate; Darrell, Trevor; A category-level 3d object dataset: Putting the kinect to work, Consumer Depth Cameras for Computer Vision, Springer London, 2013
McCann, Eric; Medvedev, Mikhail; Brooks, Daniel J; Saenko, Kate; "Off the grid": Self-contained landmarks for improved indoor probabilistic localization , Technologies for Practical Robot Applications (TePRA), 2013 IEEE International Conference on, IEEE, 2013
Krishnamoorthy, Niveda; Malkarnenkar, Girish; Mooney, Raymond; Saenko, Kate; Guadarrama, Sergio; Generating natural-language video descriptions using text-mined knowledge, NAACL HLT, 2013
Donahue, Jeff; Hoffman, Judy; Rodner, Erik; Saenko, Kate; Darrell, Trevor; Semi-supervised domain adaptation with instance constraints , Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, IEEE, 2013
Sergio Guadarrama, Niveda Krishnamoorthy, Girish Malkarnenkar, Subhashini Venugopalan, Raymond Mooney, Trevor Darrell, and Kate Saenko; Youtube2text: Recognizing and describing arbitrary activities using semantic hierarchies and zero-shot recognition. In IEEE International Conference on Computer Vision (ICCV) 2013. [dataset]
Huang, Ke; Ding, Xiang; Chen, Guanling; Saenko, Kate; Automatic mobile photo tagging using context, TENCON 2013-2013 IEEE Region 10 Conference (31194), IEEE, 2013
2012
Xiong, Ying; Saenko, Kate; Darrell, Trevor; Zickler, Todd; From pixels to physics: Probabilistic color de-rendering , Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, IEEE, 2012
Packer, Benjamin; Saenko, Kate; Koller, Daphne; A combined pose, object, and feature model for action understanding , Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, IEEE, 2012
Hoffman, Judy; Kulis, Brian; Darrell, Trevor; Saenko, Kate; Discovering latent domains for multisource domain adaptation, European Conference on Computer Vision (ECCV), 2012
Saenko, Kate; Packer, Ben; Chen, C; Bandla, S; Lee, Y; Jia, Yangqing; Niebles, J; Koller, D; Fei-Fei, L; Grauman, K; Mid-level features improve recognition of interactive activities , UC Berkeley EECS Technical Report, 2012
2011
Saenko, Kate; Karayev, Sergey; Jia, Yangqing; Shyr, Alex; Janoch, Allison; Long, Jonathan; Fritz, Mario; Darrell, Trevor; Practical 3-D object detection using category and instance-level appearance models , Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, IEEE, 2011
Hoffman, Judy; Saenko, Kate; Kulis, Brian; Darrell, Trevor; Domain adaptation with multiple latent domains, NIPS Domain Adaptation Workshop, 2011
T. Tuytelaars, M. Fritz, K. Saenko, T. Darrell, "The NBNN kernel", International Conference on Computer Vision (ICCV), 2011.
B. Kulis, K. Saenko, and T. Darrell, What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. Oral Presentation: 3.5% Acceptance Rate.
T. Owens, K. Saenko, A. Chakrabarti, Y. Xiong, T. Zickler, and T. Darrell, "Learning Object Color Models from Multi-view Constraints", In CVPR 2011.
Owens, Trevor; Saenko, Kate; Chakrabarti, Ayan; Xiong, Ying; Zickler, Todd; Darrell, Trevor; The ratio method for multi-view color constancy ,UC Berkeley Tech. Report, 2011
Xiong, Ying; Saenko, Kate; Zickler, Todd; Darrell, Trevor; Modeling the Uncertainty in Inverse Radiometric Calibration , 2011
2010
M. Fritz, K. Saenko, T. Darrell, "Size Matters: Metric Visual Search Constraints from Monocular Metadata" In Proc. NIPS, December 2010, Vancouver, Canada.
K. Saenko, B. Kulis, M. Fritz and T. Darrell,
"Adapting Visual Category Models to New Domains"
In Proc. ECCV, September 2010,
Saenko, Kate; Kulis, Brian; Fritz, Mario; Darrell, Trevor; Visual domain adaptation using regularized cross-domain transforms ,Technical Report UCB/EECS-2010-106, EECS Department, University of California, Berkeley, 2010
Saenko, Kate; Kulis, Brian; Fritz, Mario; Darrell, Trevor; Transferring visual category models to new domains ,Technical Report UCB/EECS-2010-54, EECS Department, University of California, Berkeley, 2010
2009
K. Saenko, "Image Sense Disambiguation: A Multimodal Approach." Doctoral Thesis, Massachusetts Institute of Technology. August 2009. [pdf] [slides]
K. Saenko and T. Darrell, "Filtering Abstract Senses From Image Search Results" In Proc. NIPS, December 2009,Vancouver,Canada.
K. Saenko, K. Livescu, J. Glass, and T. Darrell, "Multistream Articulatory Feature-Based Models for Visual Speech Recognition". In IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009.
2008 (and earlier)
K. Saenko and T. Darrell, "Unsupervised Learning of Visual Sense Models for Polysemous Words". Proc. NIPS, December 2008, Vancouver, Canada.
M. Hasegawa, K. Livescu, P. Lal, and K. Saenko, "Audiovisual Speech Recognition with Articulator Positions as Hidden Variables." Proc. International Congress of Phonetic Sciences, August 2007, Saarbruecken,Germany.
K. Saenko and T. Darrell, "Object Category Recognition Using Probabilistic Fusion of Speech and Image Classifiers". Proc. Machine Learning for Multimodal Interaction (MLMI), June 2007, Brno, Czech Republic.
Saenko, Kate; Darrell, Trevor; Towards adaptive object recognition for situated human-computer interaction, Proceedings of the 2007 workshop on Multimodal interfaces in semantic interaction, ACM, 2007
Karen Livescu, Ozgur Cetin, Mark Hasegawa-Johnson, Simon King, Chris Bartels, Nash Borges, Arthur Kantor, Partha Lal, Lisa Yung, Ari Bezman, Stephen Dawson-Haggerty, Bronwyn Woods, Joe Frankel, Matthew Magimai-Doss, and Kate Saenko, "Articulatory Feature-Based Methods for Acoustic and Audio-Visual Speech Recognition: Summary from the 2006 JHU Summer Workshop". ICASSP, May 2007.
K. Saenko and K. Livescu, "An Asynchronous DBN for Audio-Visual Speech Recognition". In Proc. IEEE 2006 Workshop on Spoken Language Technology (SLT), December 2006, Palm Beach, Aruba.
C. Christoudias, K. Saenko, L.-P. Morency and T. Darrell, "Co-Adaptation of Audio-Visual Speech and Gesture Classifiers". Proc. ICMI, November 2006, Banff, Canada. Best Paper Award.
Saenko, Kate; Livescu, Karen; An asynchronous DBN for audio-visual speech recognition , Spoken Language Technology Workshop, 2006. IEEE, IEEE, 2006
K. Saenko, K. Livescu, M. Siracusa, K. Wilson, J. Glass, and T. Darrell, "Visual Speech Recognition with Loosely Synchronized Feature Streams". Proc. ICCV, October 2005, Beijing.
K. Saenko, K. Livescu, J. Glass, and T. Darrell, "Production Domain Modeling of Pronunciation for Visual Speech Recognition". Proc. ICASSP, March 2005, Philadelphia.
K. Saenko, T. Darrell, and J. Glass, "Articulatory Features for Robust Visual Speech Recognition". Proc. ICMI, pp.152-158, October 2004, State College, PA.
T. Hazen, K, Saenko, C. La, and J. Glass, "A Segment-based Audio-Visual Speech Recognizer: Data Collection, Development, and Initial Experiments" . Proc. ICMI, pp. 235-242, October 2004, State College, PA.