Publications

Found 132 results
Author Title Type [ Year(Desc)]
Filters: Author is Trevor Darrell  [Clear All Filters]
2015
Darrell, T., Kloft M., Pontil M., Rätsch G., & Rodner E. (2015).  Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152). Dagstuhl Reports. 5, 18–55.
Narihira, T., Borth D., Yu S. X., Ni K., & Darrell T. (2015).  Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets.
Fisher, J., Darrell T., Galup L., How J., Krause A., & Soatto S. (2015).  Nonparametric Representations for Integrated Inference, Control, and Sensing.
Beijbom, O., Hoffman J., Yao E., Darrell T., Rodriguez-Ramirez A., Gonzalez-Rivero M., et al. (2015).  Quantification in-the-wild: data-sets and baselines. CoRR. abs/1510.04811,
Chu, V., McMahon I., Riano L., McDonald C. G., He Q., Perez-Tejada J. Martinez, et al. (2015).  Robotic Learning of Haptic Adjectives Through Physical Interaction. Robot. Auton. Syst.. 63(P3), 279–292.
Shelhamer, E., Barron J. T., & Darrell T. (2015).  Scene Intrinsics and Depth From a Single Image. The IEEE International Conference on Computer Vision (ICCV) Workshops.
Venugopalan, S., Rohrbach M., Donahue J., Mooney R., Darrell T., & Saenko K. (2015).  Sequence to Sequence - Video to Text. The IEEE International Conference on Computer Vision (ICCV).
Tzeng, E., Hoffman J., Darrell T., & Saenko K. (2015).  Simultaneous Deep Transfer Across Domains and Tasks. The IEEE International Conference on Computer Vision (ICCV). 4068-4076.
Mrowca, D., Rohrbach M., Hoffman J., Hu R., Saenko K., & Darrell T. (2015).  Spatial Semantic Regularisation for Large Scale Object Detection. The IEEE International Conference on Computer Vision (ICCV).
Tzeng, E., Devin C., Hoffman J., Finn C., Peng X., Levine S., et al. (2015).  Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. CoRR. abs/1511.07111,
Guadarrama, S., Rodner E., Saenko K., & Darrell T. (2015).  Understanding object descriptions in robotics by open-vocabulary object retrieval and detection. The International Journal of Robotics Research. 35(1-3), 265-280.
Garg, A., Krishnan S., Murali A., Pokorny F. T., Abbeel P., Darrell T., et al. (2015).  On Visual Feature Representations for Transition State Learning in Robotic Task Demonstrations. 44,
2016
Tzeng, E., Devin C., Hoffman J., Finn C., Abbeel P., Levine S., et al. (2016).  Adapting deep visuomotor representations with weak pairwise constraints. Workshop on the Algorithmic Foundations of Robotics (WAFR).
Donahue, J., Krahenbuhl P., & Darrell T. (2016).  Adversarial Feature Learning. CoRR. abs/1605.09782,
Gao, Y., Beijbom O., Zhang N., & Darrell T. (2016).  Compact Bilinear Pooling. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 317-326.
Pathak, D., Krahenbuhl P., Donahue J., Darrell T., & Efros A. A. (2016).  Context Encoders: Feature Learning by Inpainting. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2536-2544.
Hoffman, J., Gupta S., Leong J., Guadarrama S., & Darrell T. (2016).  Cross-modal adaptation for RGB-D detection. IEEE International Conference on Robotics and Automation (ICRA). 5032-5039.
Hendricks, L. Anne, Venugopalan S., Rohrbach M., Mooney R., Saenko K., & Darrell T. (2016).  Deep Compositional Captioning: Describing Novel Object Categories Without Paired Training Data. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 1-10.
Andreas, J., Rohrbach M., Darrell T., & Klein D. (2016).  Deep compositional question answering with neural module networks. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
Gao, Y., Hendricks L. Anne, Kuchenbecker K. J., & Darrell T. (2016).  Deep learning for tactile understanding from visual and haptic data. IEEE International Conference on Robotics and Automation (ICRA). 536-543.
Finn, C., Tan X. Yu, Duan Y., Darrell T., Levine S., & Abbeel P. (2016).  Deep spatial autoencoders for visuomotor learning. IEEE International Conference on Robotics and Automation (ICRA). 512-519.
Levine, S., Finn C., Darrell T., & Abbeel P. (2016).  End-to-end training of deep visuomotor policies. Journal of Machine Learning Research. 17, 1–40.
Shelhamer, E., Long J., & Darrell T. (2016).  Fully Convolutional Networks for Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 39(4), 640-651.
Hoffman, J., Pathak D., Tzeng E., Long J., Guadarrama S., Darrell T., et al. (2016).  Large Scale Visual Recognition Through Adaptation Using Joint Representation and Multiple Instance Learning. J. Mach. Learn. Res.. 17, 4954–4984.
Andreas, J., Rohrbach M., Darrell T., & Klein D. (2016).  Learning to Compose Neural Networks for Question Answering. CoRR. abs/1601.01705,

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