About Me ...
I am an Associate Professor in the Department of Computer Science at the University of British Columbia. I am also an NSERC Canada Research Chair (CRC II) in Computer Vision and Machine Learning and a CIFAR AI Chair at the Vector Institute for AI in Toronto. In addition, I serve as an Academic Advisor to Borealis AI.
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.
My full bio and CV can be found here.
News and recent activity
- I am a recipient of Killam Accelerator Fellowship.
- I am a recipient of NSERC Canada Research Chair (CRC II) in Computer Vision and Machine Learning and the NSERC DAS award.
- I am a recipient of CIFAR AI Chair.
- I am an area chair for CVPR 2022, ICML 2022, IJCAI 2022.
Press coverage
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Our work on semantic video event representation in CVPR 2016. |
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Our work on modeling action progression using LSTMs in CVPR 2016. |
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Our work on zero-shot pose estimation in AAAI 2016. |
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Our work on graph-based activity recognition in CVPR 2015. |
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Our work on story-driven photo album curation in WACV 2015. |
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Our work on body mounted camera motion capture in ACM SIGGRAPH 2011. |
Some semi-recent research highlights:
(for full least see publications)
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TriBERT: Human-centric Audio-visual Representation Learning,
T. Rahman, M. Yang and L. Sigal,
Neural Information Processing Systems (NeurIPS), 2021. |
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Referring Transformer: A One-step Approach to Multi-task Visual Grounding,
M. Li and L. Sigal,
Neural Information Processing Systems (NeurIPS), 2021. |
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Segmentation-grounded Scene Graph Generation,
S. Khandelwal*, M. Suhail* and L. Sigal,
IEEE/CVF International Conference on Computer Vision (ICCV), 2021. |
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Energy-based Learning for Scene Graph Generation,
M. Suhail, A. Mittal, B. Siddiquie, C. Broaddus, J. Eledath, G. Medioni and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. |
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UniT: Unified Knowledge Transfer for Any-shot Object Detection and Segmentation,
S. Khandelwal, R. Goyal and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. |
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Image Generation From Layout,
B. Zhao, L. Meng, W. Yin and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. |
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Modular Generative Adversarial Networks,
B. Zhao, B. Chang, Z. Jie and L. Sigal,
European Conference on Computer Vision (ECCV), 2018. |
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Visual Reference Resolution using Attention Memory for Visual Dialog,
P. H. Seo, A. Lehrmann, B. Han and L. Sigal,
Neural Information Processing Systems (NeurIPS), 2017. |
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Semi-supervised Vocabulary-informed Learning,
Y. Fu and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. |
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A Unified Semantic Embedding: Relating Taxonomies and Attributes,
S.-J. Hwang, L. Sigal,
Neural Information Processing Systems (NeurIPS), 2014. |