Found 132 results
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Journal Article
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,
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.
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,
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.
Girshick, R., Donahue J., Darrell T., & Malik J. (2016).  Region-Based Convolutional Networks for Accurate Object Detection and Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 38(1), 142-158.
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,
Saenko, K., Livescu K., Glass J. R., & Darrell T. (2009).  Multistream Articulatory Feature-Based Models for Visual Speech Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 31,
Fukui, A., Park D. Huk, Yang D., Rohrbach A., Darrell T., & Rohrbach M. (2016).  Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding. CoRR. abs/1606.01847,
Xiong, Y., Scharstein D., Chakrabarti A., Darrell T., Sun B., Saenko K., et al. (2014).  Modeling Radiometric Uncertainty for Vision with Tone-Mapped Color Images. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(11), 2185-2198.
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.
Finn, C., Tan X. Yu, Duan Y., Darrell T., Levine S., & Abbeel P. (2015).  Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders. arXiv.