Research
My PhD advisor is
Daphne Koller.
I am a member of the
DAGS Research Group,
and have interests in:
- Machine learning and AI
- Probabilistic graphical models
- Convex optimization
- Robotics and computer vision
I also do a lot of work on the
STAIR project with
Andrew Ng.
Publications*
Discriminative Learning with Latent Variables for Cluttered Indoor Scene Understanding
Huayan Wang, Stephen Gould and Daphne Koller.
In
Proceedings of the European Conference on Computer Vision (ECCV),
2010.
[
pdf |
bib]
A Unified Contour-Pixel Model for Segmentation
Ben Packer, Stephen Gould and Daphne Koller.
In
Proceedings of the European Conference on Computer Vision (ECCV),
2010.
[ pdf coming soon |
bib]
Probabilistic Models for Region-based Scene Understanding
Stephen Gould.
Ph.D. Thesis, Stanford University,
June 2010.
[
pdf |
archive |
bib]
Accelerated Dual Decomposition for MAP Inference
Vladimir Jojic, Stephen Gould and Daphne Koller.
In
Proceedings of the International Conference on Machine Learning (ICML),
2010.
[
pdf |
bib]
Single Image Depth Estimation from Predicted Semantic Labels
Beyang Liu, Stephen Gould and Daphne Koller.
In
IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
2010.
[
pdf |
bib |
data (.tar.gz)]
Region-based Segmentation and Object Detection
Stephen Gould, Tianshi Gao and Daphne Koller.
In
Advances in Neural Information Processing Systems (NIPS),
2009.
[
pdf |
bib]
Decomposing a Scene into Geometric and Semantically Consistent Regions
Alphabet SOUP: A Framework for Approximate Energy Minimization
Stephen Gould, Fernando Amat and Daphne Koller.
In
IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
2009.
[
pdf |
poster |
bib]
High-Accuracy 3D Sensing for Mobile Manipulation: Improving Object Detection and Door Opening
Morgan Quigley, Siddharth Batra, Stephen Gould, Ellen Klingbeil, Quoc V. Le, Ashley Wellman and Andrew Y. Ng.
In
IEEE International Conference on Robotics and Automation (ICRA),
2009.
[
pdf |
videos |
bib]
Cascaded Classification Models: Combining Models for Holistic Scene Understanding
Geremy Heitz, Stephen Gould, Ashutosh Saxena and Daphne Koller.
In
Advances in Neural Information Processing Systems (NIPS),
2008.
[
pdf |
bib]
Learning Bounded Treewidth Bayesian Networks
Gal Elidan and Stephen Gould.
In
Advances in Neural Information Processing Systems (NIPS),
2008.
A longer version of this paper also appears
in
Journal of Machine Learning Research (JMLR),
2008.
[
pdf (nips) |
pdf (jmlr) |
bib]
Integrating Visual and Range Data for Robotic Object Detection
Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller.
In
ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2),
2008.
[
pdf |
bib]
Projected Subgradient Methods for Learning Sparse Gaussians
John Duchi, Stephen Gould and Daphne Koller.
In
Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI),
2008.
[
pdf |
bib]
Multi-Class Segmentation with Relative Location Prior
Stephen Gould, Jim Rodgers, David Cohen, Gal Elidan and Daphne Koller.
In
International Journal of Computer Vision (IJCV),
2008.
[
pdf |
code |
bib]
STAIR: The STanford Artificial Intelligence Robot Project
Andrew Y. Ng, Stephen Gould, Morgan Quigley, Ashutosh Saxena and Eric Berger.
In
Learning Workshop, Snowbird,
2008.
[
project]
Peripheral-Foveal Vision for Real-time Object Recognition and Tracking in Video
Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp,
Marius Meissner, Gary Bradski, Paul Baumstarck, Sukwon Chung and Andrew Y. Ng.
In
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI),
2007.
[
pdf |
bib]
* Since most of these
papers are published in journals and conferences, the copyright has
been transferred to the respective publishers. Those papers cannot be
duplicated for commercial purposes.
Demonstrations
High-Accuracy 3D Sensing for Mobile Manipulators
Morgan Quigley, Siddharth Batra, Stephen Gould, Ellen Klingbiel, Quoc V. Le
and Andrew Y. Ng.
In
Advances in Neural Information Processing Systems (NIPS), 2008.
[
videos |
poster]
Holistic Scene Understanding from Visual and Range Data
Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller.
In
Advances in Neural Information Processing Systems (NIPS), 2007.
[
videos |
poster]
Peripheral-Foveal Vision for Real-time Object Recognition and Tracking in Video
Stephen Gould, Benjamin Sapp, Morgan Quigley and Andrew Y. Ng.
In
Advances in Neural Information Processing Systems (NIPS), 2006.
[
videos |
poster]
Software
The STAIR Vision Library
A platform independent C++ toolkit for computer vision research
(building on top of OpenCV). The library also includes many machine
learning and probabilistic graphical models algorithms. We have released
the code under the BSD license. Many of the algorithms described in the
papers above are implemented in this codebase.
[
wiki |
doc |
sourceforge]
Activities
Conferences and Journals
Program committee member for Robotics: Science and Systems (RSS): 2010.
Program committee member for International Conference on Machine Learning (ICML): 2010.
Program committee member for Conference on Uncertainty in AI (UAI): 2008, 2009.
Panel member for 1st International Workshop on Visual Scene Understanding (ViSU), 2009.
Reviewer for Advances in Neural Information Processing Systems (NIPS): 2010.
Reviewer for Journal of Machine Learning Research (JMLR): 2009.
Reviewer for IEEE Conference on Computer Vision and Pattern Recognition (CVPR): 2010.
Reviewer for International Conference for Computer Vision (ICCV): 2009.
Reviewer for European Conference on Computer Vision (ECCV): 2010.
Reviewer for IEEE Journal of Selected Topics in Signal Processing: 2010.
Reviewer for IEEE Transactions on Image Processing: 2010.
Invited Talks
Invited talk titled “Probabilistic Models in Holistic Scene Understanding” given at
Stanford Computer Science Faculty Luncheon, 2010.
Invited talk titled “A Region-based Approach to Scene Understanding” given at
The First IEEE Workshop on Visual Place Categorization (VPC), 2009.
Invited talk titled “Multi-modal Robotic Vision: Detecting Objects and People”
at Honda Research Institute, April 2008.
Teaching
Teaching assistant for
CS294A: Projects in Holistic Scene Understanding (Autumn 2009)
Teaching assistant for
CS294A: Research Projects in Artificial Intelligence (Autumn 2008)
Teaching assistant for
CS294A: STAIR: STanford AI Robot Project (Winter 2008)
Teaching assistant for
CS228: Probabilistic Models in AI (Winter 2008)
Teaching assistant for
CS228: Probabilistic Models in AI (Winter 2007)
Issued Patents
US 7,725,312.
Transcoding method and system between CELP-based speech codes with externally provided status.
US 7,411,418.
Efficient representation of state transition tables.
US 7,301,792.
Apparatus and method of ordering state transition rules for memory efficient, programmable, pattern matching finite state machine hardware.
US 7,219,319.
Apparatus and method for generating state transition rules for memory efficient programmable pattern matching finite state machine hardware.
US 7,184,953.
Transcoding method and system between CELP-based speech codes with externally provided status.
US 7,180,328.
Apparatus and method for large hardware finite state machine with embedded equivalence classes.
US 7,082,044.
Apparatus and method for memory efficient, programmable, pattern matching finite state machine hardware.
US 6,829,579.
Transcoding method and system between CELP-based speech codes.
AU 2004222859.
A method for developing algorithms.
Useful Links
