Publications

Found 132 results
Author Title [ Type(Desc)] Year
Filters: Author is Trevor Darrell  [Clear All Filters]
Conference Paper
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).
Saenko, K., Kulis B., Fritz M., & Darrell T. (2010).  Adapting Visual Category Models to New Domains. 213-226.
Fritz, M., Black M., Bradski G., & Darrell T. (2009).  An Additive Latent Feature Model for Transparent Object Recognition. 558-566.
Fritz, M., Black M., Bradski G., Karayev S., & Darrell T. (2009).  An Additive Latent Feature Model for Transparent Object Recognition.
Karayev, S., Fritz M., & Darrell T. (2014).  Anytime Recognition of Objects and Scenes.
Jia, Y., Huang C., & Darrell T. (2012).  Beyond Spatial Pyramids: Receptive Field Learning for Pooled Image Features. 3370-3377.
Farrell, R., Oza O., Zhang N., Morariu V. I., Darrell T., & Davis L. S. (2011).  Birdlets: Subordinate Categorization Using Volumetric Primitives and Pose-Normalized Appearance. 161-168.
Jia, Y., Shelhamer E., Donahue J., Karayev S., Long J., Girshick R., et al. (2014).  Caffe: Convolutional Architecture for Fast Feature Embedding. 675-678.
Janoch, A., Karayev S., Jia Y., Barron J. T., Fritz M., Saenko K., et al. (2011).  A Category-Level 3-D Object Dataset: Putting the Kinect to Work. 1168-1174.
Gao, Y., Beijbom O., Zhang N., & Darrell T. (2016).  Compact Bilinear Pooling. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 317-326.
Jia, Y., Vinyals O., & Darrell T. (2013).  On Compact Codes for Spatially Pooled Features.
Pathak, D., Krahenbuhl P., & Darrell T. (2015).  Constrained Convolutional Neural Networks for Weakly Supervised Segmentation. The IEEE International Conference on Computer Vision (ICCV). 1796-1804.
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., Darrell T., & Saenko K. (2014).  Continuous Manifold Based Adaptation for Evolving Visual Domains.
C. Christoudias, M., Urtasun R., Kapoor A., & Darrell T. (2009).  Co-Training with Noisy Perceptual Observations. 2844-2851.
Donahue, J., Jia Y., Vinyals O., Hoffman J., Zhang N., Tzeng E., et al. (2014).  DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition.
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).
Zhang, N., Farrell R., Iandola F., & Darrell T. (2013).  Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction.
Girshick, R., Iandola F., Darrell T., & Malik J. (2015).  Deformable Part Models are Convolutional Neural Networks. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 437-446.
Althoff, T., Song H. Oh, & Darrell T. (2012).  Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition.
Hoffman, J., Pathak D., Darrell T., & Saenko K. (2015).  Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2883-2891.
Hoffman, J., Saenko K., Kulis B., & Darrell T. (2012).  Discovering Latent Domains for Multisource Domain Adaptation. 702-715.
Girshick, R., Song H. Oh, & Darrell T. (2013).  Discriminatively Activated Sparselets.
Yeh, T., & Darrell T. (2008).  Dynamic Visual Category Learning.

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