Sanja Fidler
Appointment
Canada CIFAR AI Chair
Pan-Canadian AI Strategy
About
Sanja Fidler is a Canada CIFAR AI Chair at the Vector Institute, an associate professor in the department of mathematical and computational sciences at the University of Toronto, and the director of AI at NVIDIA.
Fidler’s work is in the area of computer vision. Her main research interests are 2D and 3D object detection, particularly scalable multi-class detection, object segmentation and image labeling, and (3D) scene understanding. Fidler is also interested in the interplay between language and vision: generating sentential descriptions about complex scenes, as well as using textual descriptions for better scene parsing (e.g., in the scenario of the human-robot interaction).
Awards
- Best Paper Honorable Mention, CVPR, 2017
- Amazon Academic Research Award, 2017
- NVIDIA Pioneer of AI Award, 2016
- Facebook Faculty Award, 2016
- Outstanding Reviewer Award, ECCV (2008, 2012) and CVPR (2012, 2015)
Relevant Publications
Zhou, B., Zhao, H., Puig, X., Xiao, T., Fidler, S., Barriuso, A., & Torralba, A. (2019). Semantic understanding of scenes through the ade20k dataset. International Journal of Computer Vision, 127(3), 302-321.
Damen, D., Doughty, H., Farinella, G. M., Fidler, S., Furnari, A., Kazakos, E., … & Wray, M. (2018). Scaling egocentric vision: The epic-kitchens dataset. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 720-736).
Zhou, B., Zhao, H., Puig, X., Fidler, S., Barriuso, A., & Torralba, A. (2017). Scene parsing through ade20k dataset. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 5122-5130).
Kiros, R., Zhu, Y., Salakhutdinov, R. R., Zemel, R., Urtasun, R., Torralba, A., & Fidler, S. (2015). Skip-thought vectors. In Advances in neural information processing systems (pp. 3294-3302).
Zhu, Y., Kiros, R., Zemel, R., Salakhutdinov, R., Urtasun, R., Torralba, A., & Fidler, S. (2015). Aligning books and movies: Towards story-like visual explanations by watching movies and reading books. In Proceedings of the IEEE international conference on computer vision (pp. 19-27).
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