Prof. Trevor Darrell

 

Berkeley Vision and Learning Center,

CS Division, EECS Dept., University of California, Berkeley, CA,

International Computer Science Institute, Berkeley, CA.

Description: Description: Description: Description: C:\Users\trevor\Dropbox\t3\etc\homepage\trevordarrell.jpg


Prof. Trevor Darrell’s group is co-located at the University of California, Berkeley (UCB), and the UCB-affiliated International Computer Science Institute (ICSI), also located in Berkeley, CA. Prof. Darrell is the faculty director of the Berkeley Vision and Learning Center in the EECS Department at UCB and is the vision group director at ICSI. Darrell’s group develops algorithms to enable multimodal conversation with robots and mobile devices, and methods for object and activity recognition on such platforms. His interests include computer vision, machine learning, computer graphics, and perception-based human computer interfaces. Prof. Darrell was previously on the faculty of the MIT EECS department from 1999-2008, where he directed the Vision Interface Group. He was a member of the research staff at Interval Research Corporation from 1996-1999, and received the S.M., and PhD. degrees from MIT in 1992 and 1996, respectively. He obtained the B.S.E. degree from the University of Pennsylvania in 1988, having started his career in computer vision as an undergraduate researcher in Ruzena Bajcsy's GRASP lab.


 

Current Teaching

 

CS294: Object and Activity Recognition Seminar (Spring 2014)

 

CS294: Object and Activity Recognition Seminar (Spring 2013)

 

CS294: Object and Activity Recognition Seminar (Spring 2012)

  

CS294: Object and Activity Recognition Seminar (Spring 2011)

  

CS280: Computer Vision (Fall 2009) 

  

CS294: Object and Activity Recognition Seminar (Spring 2009)

 


Recent Presentations

 

      Sept 2012 BAVM Invited Talk (pdf) (pptx)

      Sept 2011 IROS Invited Talk

      May 2010 UCB EECS Colloquium

 

 


Publications — (CURRENT through ICML 2013; I will update this page eventually, but for more recent publications click here for google scholar page and sort by year.)

                                                                      

Y. Jia, O. Vinyals, T. Darrell. On Compact Codes for Spatially Pooled Features. ICML 2013

H. O. Song, R. Girshick, T. Darrell, Discriminatively Activated Sparselets, ICML 2013

J. Donahue, J. Hoffman, E. Rodner, K. Saenko, 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.

Z. Stone, T. Zickler, and T. Darrell, Autotagging Facebook: Social Network Context Improves Photo Annotation,   IEEE Workshop on Internet Vision 2008.

 

 

Older publications: http://www.eecs.berkeley.edu/~trevor/Publications.htm

 

  

  


 

 

 

Darrell Group (UCB/ICSI) – (Group Spotlight Presentations)

Research Scientist:

 

Dr. Ryan Farrell

Postdocs:

     Dr. Stefanie Jegelka (Joint with Mike Jordan)

     Dr. Lorenzo Riano (Joint with Pieter Abbeel)

     Dr. Daniel Goehring

     Dr. Sergio Guardarrama

     Dr. Erik Rodner

Affiliated Postdocs:

     Dr. Ross Girshick (Malik group)

PhD Students: 

Sergey Karayev

Yanqqing Jia

Hyun Oh Song

Oriol Vinyals

Ning Zhang

Jon Long

Judy Hoffman

Jeff Donahue

Evan Shelhammer

 


 

 

 

Previous Postdocs (not including former students)

     Dr. Brian Kulis

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

 

Graduated PhD. Students:

Alex Shyr, Incorporating Supervision for Visual Recognition and Segmentation, Sept 2011 [Startup]

 

Ashley Eden, Finding Lost Children, Dec 2010 [Dreamworks]

Mario Christoudas, Probabilistic Models for Semi-Supervised Learning and Coding, Aug 2009 [Postdoc, EPFL]

Kate Saenko, Image Sense Disambiguation: A Multimodal Approach, Aug 2009 [Faculty UML]

Tom Yeh, Interacting with Computers using Images for Search and Automation, May 2009 [Postdoc, UMD]

Ariadna Quattoni, Transfer Learning Algorithms for Image Classification, May 2009 [Postdoc, Barcelona]

Sy Bor Wang, Communication Error Detection Using Facial Expressions, May 2008 [Research Scientist, Trimble Navigations]

 

Louis-Philippe Morency, Dialogue Context and Visual Gesture Recognition, Oct 2006 [Research Scientist, USC]

 

Kristen Grauman, Matching sets of features for efficient retrieval and recognition, Aug. 2006 [Assistant Professor, CS, University of Texas, Austin]

 

Leonid Taycher, Statistical methods for dynamic visual processing, Aug 2006 [Google Boston]

 

Kevin Wilson, Learning Uncertainty Models for Audiovisual Speech Source Localization in Real-World Environments, Aug 2006 [Research Scientist, MERL]

 

Gregory Shakhnarovich, Learning Features for Visual Classification, Oct. 2005 [Assistant Professor, TTI-C]

 

Ali Rahimi, Learning to Transform Time Series with a Few Examples, Oct. 2005 [Intel Research Laboratories, Berkeley]

 

Graduated MS Students:

Allie Janoch

Trevor Owens

 

 Previous Graduate Visitors:

Tim Althoff

 

Tobias Baumgartner

 

 


 

 

 

 

 

 

 

Previous Classes:

Fall 2009 (Berkeley): CS280: Computer Vision

Spring 2009 (Berkeley): CS294-43: Object Recognition Seminar

Spring 2007: 6.870: Intelligent Multimodal Interfaces

Spring 2006: 6.001 Lectures

Fall 2005: 6.897 Object Recognition Seminar

Spring 2005: 6.001 Lectures

Fall 2004: 6.001 Recitation

Spring 2004: 6.891 Computer Vision and Applications

Fall 2002: 6.801/6.866 Computer Vision

Spring 2002: 6.001 Recitation

Fall 2001: (6.892) Computer Vision for Interface and Surveillance: Algorithms and Implications

Spring 2001: 6.001 Recitation

Fall 2000:  (6.892) Computer Vision for Interface and Surveillance: Algorithms and Implications

Spring 2000: Vision Interface Reading Group.

Spring 2000: 6.001 Recitation

(Stanford) Spring 1997: CS377B; Machine Perception for Human-Computer Interface, under Terry Winograd's PCD program in the Department of Computer Science.

 


 

 

 

 

 

 

 

Previous Project pages:

MIT CSAIL Vision Interfaces Group (1999-2008) 

MIT Media Lab / Interval Research Corp. (1987-2001)


 

 

 

 

 

 

 

Meetings Organized:

Summer 2010 – CVPR 2010 (Program Chair)

Spring 2010 – BAVM 2010, UCB

Spring 2007 - ISAT study on Exploitation of Persistent Operational Surveillance (Chair)

Spring 2006 - ISAT quick reaction study on Adaptive and Interactive Representations (Co-Chair)

Fall 2004 - ICMI 2004 (General Chair)

Fall 2003 - NIPS Workshop on Approximate Nearest Neighbors Methods for Learning and Vision

Fall 2003 - ICMI 2003 (Program Chair)

Fall 2001 - NIPS Workshop on Multi-Sensory Perceptive Systems

Fall 2001 - PUI 2001 (Program Chair)

Fall 98 / Spring 99 - Interval Research Signal Computation Seminar

May 98 - Third Bay Area Vision Meeting (BAVM)