Found 17 results
Author Title [ Type(Desc)] Year
Filters: Author is Jeff Donahue  [Clear All Filters]
Conference Paper
Jia, Y., Shelhamer E., Donahue J., Karayev S., Long J., Girshick R., et al. (2014).  Caffe: Convolutional Architecture for Fast Feature Embedding. 675-678.
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.
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.
Hoffman, J., Rodner E., Donahue J., Darrell T., & Saenko K. (2013).  Efficient Learning of Domain-Invariant Image Representations.
Donahue, J., Hendricks L. Anne, Guadarrama S., Rohrbach M., Venugopalan S., Saenko K., et al. (2015).  Long-Term Recurrent Convolutional Networks for Visual Recognition and Description.
Guadarrama, S., Rodner E., Saenko K., Zhang N., Farrell R., Donahue J., et al. (2014).  Open-Vocabulary Object Retrieval.
Zhang, N., Donahue J., Girshick R., & Darrell T. (2014).  Part-Based R-CNNs for Fine-Grained Category Detection.
Rodner, E., Hoffman J., Donahue J., Darrell T., & Saenko K. (2013).  Scalable Transform-Based Domain Adaptation.
Donahue, J., Hoffman J., Rodner E., Saenko K., & Darrell T. (2013).  Semi-Supervised Domain Adaptation with Instance Constraints.
Rodner, E., Hoffman J., Donahue J., Darrell T., & Saenko K. (2013).  Transform-Based Domain Adaptation for Big Data.
Venugopalan, S., Xu H., Donahue J., Rohrbach M., Mooney R., & Saenko K. (2015).  Translating Videos to Natural Language Using Deep Recurrent Neural Networks.
Journal Article
Donahue, J., Krahenbuhl P., & Darrell T. (2016).  Adversarial Feature Learning. CoRR. abs/1605.09782,
Krahenbuhl, P., Doersch C., Donahue J., & Darrell T. (2015).  Data-dependent Initializations of Convolutional Neural Networks. CoRR. abs/1511.06856,
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.