Prof. Trevor Darrell
CS Division, University of California, Berkeley, CA, and the
International Computer Science Institute, Berkeley, CA.
Director, Berkeley Vision and Learning Center
· CAFFE – Open Source Deep Learning; Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, Trevor Darrell
· LSDA – Large Scale Detector Adaptation; Judy Hoffman, Sergio Guadarrama, Eric Tzeng, Jeff Donahue, Ross Girshick, Trevor Darrell, Kate Saenko
· RAPTOR – Interactive Detector Learning; Daniel Göhring and Judy Hoffman and Erik Rodner and Kate Saenko, and Trevor Darrell
· DECAF: A deep convolutional activation feature for generic visual recognition; Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, Trevor Darrell
· On learning to localize objects with minimal supervision; Hyun Oh Song, Ross Girshick, Stefanie Jegelka, Julien Mairal, Zaid Harchaoui, Trevor Darrell
2013 and Prior:
S. Guadarrama, N. Krishnamoorthy, G. Malkarnenkar, S. Venugopalan, R. Mooney, T. Darrell, K. Saenko, YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-shot Recognition, ICCV 2013
Y. Jia and T. Darrell, Latent Task Adaptation with Large-Scale Hierarchies, ICCV 2013
N. Zhang, R. Farrell, F. Iandola, T. Darrell, Deformable part descriptors for fine-grained recognition and attribute prediction, ICCV 2013
Y. Jia, J T Abbott, J. Austerweil, T. Griffiths, T. Darrell, Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies, NIPS 2013
Y. Jia, O. Vinyals, and T. Darrell. On Compact Codes for Spatially Pooled Features. ICML 2013
H. O. Song, R. Girshick, and T. Darrell, Discriminatively Activated Sparselets, ICML 2013
J. Donahue, J. Hoffman, E. Rodner, K. Saenko, and T. Darrell, Semi-Supervised Domain Adaptation with Instance Constraints, CVPR 2013
V. Chu, I. McMahon, L. Riano, C. G. McDonald, Q. He, J. Perez-Tejada, M. Arrigo, N. Fitter, J. Nappo, T. Darrell, and K. J. Kuchenbecker. Using
robotic exploratory procedures to learn the meaning of haptic adjectives. ICRA 2013. Best Cognitive Robotics Paper Award
J. Hoffman, E. Rodner, J. Donahue, T. Darrell, K. Saenko, Efficient Learning of Domain-invariant Image Representations, ICLR 2013 Conference
O. Vinyals, Y. Jia, T. Darrell, Why Size Matters: Feature Coding as Nystrom Sampling, ICLR 2013 Workshop
S. Karayev, M. Fritz, T. Darrell, Timely Object Recognition, NIPS 2012
O. Vinyals, Y. Jia, L. Deng, T. Darrell, Learning with Recursive Perceptual Representations, NIPS 2012
S. Chung, C. Christoudias, T. Darrell, S. Ziniel, L. Kalish, A Novel Image Based Tool to Reunite Children with Their Families after Disasters, AEMJ
T. Althoff, H. O. Song, T. Darrell, Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition, ACM MM 2012
J. Hoffman, B. Kulis, T. Darrell, K. Saenko, Discovering Latent Domains for Multisource Domain Adaptation ECCV 2012
H. O. Song, S. Zickler, T. Althoff, R. Girshick, M. Fritz, C. Geyer, P. Felzenszwalb, T. Darrell, Sparselet Models for Efficient Multiclass Object Detection, ECCV 2012
S. Miller, J. Van Den Berg, M. Fritz, T. Darrell, K. Goldberg, P. Abbeel, A geometric approach to robotic laundry folding, IJRR 2012
S. Virtanen, Y. Jia, A. Klami, T. Darrell. Factorized Multi-modal Topic Model. UAI 2012
Y. Xiong, K. Saenko, T. Zickler, T. Darrell, From Pixels to Physics: Probabilistic Color De-rendering, CVPR 2012.
N. Zhang, R. Farrell, T. Darrell. Pose Pooling Kernels for Sub-category Recognition. CVPR 2012
Y. Jia, C. Huang, T. Darrell. Beyond Spatial Pyramids: Receptive Field Learning for Pooled Image Features CVPR 2012
Y. Jia and T. Darrell, Heavy-tailed Distances for Gradient Based Image Descriptors, NIPS 2011
R. Farrell, O. Oza, N. Zhang, V. Morariu, T. Darrell, and L. Davis, Birdlets: Subordinate Categorization Using Volumetric Primitives and Pose-Normalized Appearance, ICCV 2011.
T. Tuytelaars, M. Fritz, K. Saenko, and T. Darrell, The NBNN Kernel, ICCV 2011.
Y. Jia, M. Salzmann, and T. Darrell, Learning Cross-modality Similarity for Multinomial Data, ICCV 2011.
S. Karayev, A. Janoch, Y. Jia, J. Barron, M. Fritz, K. Saenko, and T. Darrell, A Category-level 3-D Database: Putting the Kinect to Work, in ICCV 2011 Workshop on Consumer Depth Cameras for Computer Vision, 2011.
H. O. Song, M. Fritz, C. Gu and T. Darrell, Visual Grasp Affordances From Appearance-Based Cues, ICCV Workshop on Challenges and Opportunities in Robot Perception, 2011
P. Wang, S. Miller, M. Fritz, T. Darrell, and P. Abbeel, Perception for the Manipulation of Socks, IROS 2011.
K. Saenko, Y. Jia, M. Fritz, J. Long, A. Janoch, A. Shyr, S. Karayev and T. Darrell, Practical 3-D Object Detection Using Category and Instance-Level Appearance Models, IROS 2011
S. Miller, M. Fritz, T. Darrell, and P. Abbeel, Parametrized Shape Models for Clothing, ICRA 2011.
S. Karayev, M. Fritz, S. Fidler, and T. Darrell, A Probabilistic Model for Recursive Factorized Image Features, CVPR 2011.
B. Kulis, K. Saenko, and T. Darrell, What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms, CVPR 2011.
A. Shyr, T. Darrell, M. Jordan, and R. Urtasun, Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation, CVPR 2011.
T. Owens, K. Saenko, A. Chakrabarti, Y. Xiong, T. Zickler, and T. Darrell. Learning Object Color Models from Multi-view Constraints, CVPR 2011.
A. Eden, M. Christoudias, and T. Darrell, Finding Lost Children, POV 2011.
Y. Jia, M. Salzmann, and T. Darrell, Factorized Latent Spaces with Structured Sparsity, NIPS 2010.
M. Fritz, K. Saenko, and T. Darrell, Size Matters: Metric Visual Search Constraints from Monocular Metadata, NIPS 2010.
G. Friedland, O. Vinyals, and T. Darrell, Multimodal Location Estimation. ACM Multimedia 2010.
K. Saenko, B. Kulis, M. Fritz, and T. Darrell, Adapting Visual Category Models to New Domains, ECCV 2010.
M. Christoudias, R. Urtasun, M. Salzmann, and T. Darrell, Learning to Recognize Objects from Unseen Modalities, ECCV 2010.
A. Kapoor, K. Grauman, R. Urtasun, and T. Darrell, Gaussian Processes for Object Categorization, IJCV, 2010.
M. Salzmann, C. H. Ek, R. Urtasun, and T. Darrell. Factorized orthogonal latent spaces. UAI 2010.
M. Fritz, M. Black, G. Bradski, and T. Darrell, An Additive Latent Feature Model for Transparent Object Recognition, NIPS 2009.
Z. Stone, T. Zickler, and T. Darrell, Toward Large-Scale Face Recognition Using Social Network Context, Proc. of the IEEE 2010
B. Kulis and T. Darrell, Learning to Hash with Binary Reconstructive Embeddings, NIPS 2009.
K. Saenko and T. Darrell, Filtering Abstract Senses From Image Search Results, NIPS 2009.
A. Quattoni, X. Carreras, M. Collins, and T. Darrell, An Efficient Projection for L-1/L-Infinity Regularization, ICML 2009.
T. Yeh and T. Darrell, Fast Concurrent Object Localization and Recognition, CVPR 2009.
M. Christoudias, R. Urtasun, A. Kapoor and T. Darrell, Co-training with Noisy Perceptual Observations, CVPR 2009.
A. Geiger, R. Urtasun, and T. Darrell, Rank Priors for Continuous Non-Linear Dimensionality Reduction, CVPR 2009.
M. Frampton, R. Fernandez, P. Ehlen, M. Christoudias, T. Darrell, and S. Peters (2009) Who is ``You? Combining Linguistic and Gaze Features to Resolve Second-Person References in Dialogue, EACL 2009.
K. Saenko, K. Livescu, J. Glass, and T. Darrell, Multistream Articulatory Feature-Based Models for Visual Speech Recognition, TPAMI 2009
K. Saenko, and T. Darrell, Unsupervised Learning of Visual Sense Models for Polysemous Word, NIPS 2008.
T. Yeh, J. Lee, and T. Darrell, Photo-based Question Answering, ACM Multimedia 2008.
T. Yeh, and T. Darrell, Multimodal Question Answering for Mobile Devices, IUI 2008.
M. Christoudias, R. Urtasun and T. Darrell, Multi-View Learning in the Presence of View Disagreement, UAI 2008.
R. Urtasun, D. J. Fleet, A. Geiger, J. Popovic, T. Darrell and N. D. Lawrence, Topologically-Constrained Latent Variable Models, ICML 2008.
M. Christoudias, R. Urtasun and T. Darrell, Unsupervised Feature Selection via Distributed Coding for Multi-view Object Recognition, CVPR 2008.
A. Quattoni, M. Collins, and T. Darrell, Transfer Learning for Image Classification with Sparse Prototype Representations, CVPR 2008.
T. Yeh, J. Lee, and T. Darrell, Dynamic Visual Category Learning, CVPR 2008.
R. Urtasun, and T. Darrell, Sparse probabilistic regression for activity-independent human pose inference, CVPR 2008.
T. Yeh, J. Lee, and T. Darrell, Scalable classifiers for Internet vision tasks, IEEE Workshop on Internet Vision 2008.
Older publications: http://www.eecs.berkeley.edu/~trevor/Publications.htm
Dr. Eric Rodner
Dr. Ryan Farrell
Dr. Lorenzo Riano
Dr. Daniel Goehring
Dr. David Demirdjian
Dr. Raquel Urtasun
Dr. Mario Fritz
Dr. Matthieu Salzmann
Dr. Sanja Fidler (visiting)
Dr. Nicholas Cebron
Dr. Carl Ek
Dr. Peer Stelldinger
Alex Shyr, Incorporating Supervision for Visual Recognition and Segmentation, Sept 2011 [Startup]
Ashley Eden, Finding Lost Children, Dec 2010 [Dreamworks]