Skip to content
CIFAR header logo
fr
menu_mobile_logo_alt
  • News
  • Events
    • Public Events
    • Invitation-only Meetings
  • Programs
    • Research Programs
    • Pan-Canadian AI Strategy
    • Next Generation Initiatives
  • People
    • Fellows & Advisors
    • CIFAR Azrieli Global Scholars
    • Canada CIFAR AI Chairs
    • AI Strategy Leadership
    • Solution Network Members
    • Leadership
  • Support Us
  • About
    • Our Story
    • CIFAR 40
    • Awards
    • Partnerships
    • Publications & Reports
    • Careers
    • Staff Directory
    • Equity, Diversity & Inclusion
  • fr
  • Home
  • Bio

Follow Us

leonidsigal_bw

Leonid Sigal

Appointment

Canada CIFAR AI Chair

Pan-Canadian AI Strategy

Connect

University of British Columbia

Google Scholar

About

Leonid Sigal is a Canada CIFAR AI Chair at the Vector Institute, an associate professor in the department of computer science at the University of British Columbia, and a scientific advisor for Borealis AI.

Sigal’s research interests are primarily in computer vision, machine learning, and computer graphics. His research focuses on problems of visual and multi-modal (visual, textural, auditory) understanding and reasoning, including object recognition, scene understanding, articulated motion capture, action recognition, representation learning, manifold learning, transfer learning, character, and cloth animation.

Awards

  • Recipient of NSERC Discovery Accelerator Supplement, 2018-2021
  • Best Paper Award, IEEE Winter Conference of Applications of Computer Vision, 2018

Relevant Publications

  • Ma, S., Sigal, L., & Sclaroff, S. (2016). Learning activity progression in lstms for activity detection and early detection. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1942-1950).

  • Raptis, M., & Sigal, L. (2013). Poselet key-framing: A model for human activity recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2650-2657).

  • Sigal, L., Balan, A. O., & Black, M. J. (2010). Humaneva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion. International journal of computer vision, 87(1-2), 4.

  • Sigal, L., Bhatia, S., Roth, S., Black, M. J., & Isard, M. (2004). Tracking loose-limbed people. In Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. (Vol. 1, pp. I-I). IEEE.

Institution

Borealis AI

University of British Columbia

Vector Institute

Department

School of Engineering

Education

  • PhD (Computer Science), Brown University

Country

Canada

Support Us

CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.

Donate Now
CIFAR header logo

MaRS Centre, West Tower
661 University Ave., Suite 505
Toronto, ON M5G 1M1 Canada

Contact Us
Media
Careers
Accessibility Policies
Supporters
Financial Reports
Subscribe

  • © Copyright 2023 CIFAR. All Rights Reserved.
  • Charitable Registration Number: 11921 9251 RR0001
  • Terms of Use
  • Privacy
  • Sitemap

Subscribe

Stay up to date on news & ideas from CIFAR.

This website stores cookies on your computer. These cookies are used to collect information about how you interact with our website and allow us to remember you. We use this information in order to improve and customize your browsing experience and for analytics and metrics about our visitors both on this website and other media. To find out more about the cookies we use, see our Privacy Policy.
Accept Learn more