Leonid Sigal

Associate Professor, University of British Columbia

 
 
 

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Dep. of Computer Science
University of British Columbia
ICCS 119
2366 Main Mall
Vancouver, B.C. V6T 1Z4
CANADA

Phone: 1-604-822-4368
Email: lsigal at cs.ubc.ca

About Me ...

Leonid Sigal's Photo

I am an Associate Professor in the Department of Computer Science at the University of British Columbia. Prior to this I was a Senior Research Scientist at Disney Research Pittsburgh and an Adjunct Faculty member at Carnegie Mellon University. My research focuses on problems of visual understanding and reasoning. This includes object recognition, scene understanding, articulated motion capture, motion modeling, action recognition, motion perception, manifold learning, transfer learning, character and cloth animation and a number of other directions on the intersection of computer vision, machine learning, and computer graphics.

I also try to maintain an active professional service within the community. I have orginized a number of workshops and tutorials. My full bio and CV can be found here.

News and recent activity

Press coverage

Our work on semantic video event representation in CVPR 2016.

Our work on modeling action progression using LSTMs in CVPR 2016.

Our work on zero-shot pose estimation in AAAI 2016.

Our work on graph-based activity recognition in CVPR 2015.

Our work on story-driven photo album curation in WACV 2015.

Our work on body mounted camera motion capture in ACM SIGGRAPH 2011.

Some recently accepted papers:

(for full least see publications)

A Neural Multi-sequence Alignment TeCHnique (NeuMATCH), P. Dogan, B. Li, L. Sigal and M. Gross, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
Paper: [pdf]

Show Me a Story: Towards Coherent Neural Story Illustration, H. Ravi, L. Wang, C Muniz, L. Sigal, D. Metaxas and M. Kapadia, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
Paper: [pdf]

Non-parametric Structured Outputs Networks, A. Lehrmann and L. Sigal, Neural Information Processing Systems (NIPS), 2017.
Paper: [pdf]

Visual Reference Resolution using Attention Memory for Visual Dialog, A. Lehrmann and L. Sigal, Neural Information Processing Systems (NIPS), 2017.
Paper: [pdf]

Weakly-supervised Visual Grounding of Phrases with Linguistic Structures, F. Xiao, L. Sigal and Y. J. Lee, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
Paper: [pdf]

Story Albums: Creating Fictional Stories from Personal Photograph Sets, O. Radiano, Y. Graber, M. Mahler, L. Sigal and A. Shamir, Computer Graphics Forum, Volume 36, 2017. (accepted)
Paper: [pdf]

Learn How to Choose: Independent Detectors versus Composite Visual Phrases, G. Rozenthal, A. Shamir and L. Sigal, Winter Conference on Applications of Computer Vision (WACV), 2017.
Paper: [pdf]

Semi-supervised Vocabulary-informed Learning, Y. Fu and L. Sigal, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
Paper: [pdf]

Learning Activity Progression in LSTMs for Activity Detection and Early Detection, S. Ma, L. Sigal and S. Sclaroff, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
Paper: [pdf]

Harnessing Object and Scene Semantics for Large-Scale Video Understanding, Z. Wu, Y. Fu, Y.-G. Jiang and L. Sigal, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
Paper: [pdf]

Exploiting View-Specific Appearance Similarities Across Classes for Zero-shot Pose Prediction: A Metric Learning Approach, A. Kuznetsova, S. Hwang, B. Rosenhahn and L. Sigal, AAAI Conference on Artificial Intelligence (AAAI), 2016.
Paper: [pdf]

A Unified Semantic Embedding: Relating Taxonomies and Attributes, S.-J. Hwang, L. Sigal, Neural Information Processing Systems (NIPS), 2014.
Download: [pdf]

Selected publications

Organized tutorials

Organized workshops