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Paper Accepted at the 14th ACM SIGGRAPH Conference on Motion, Interaction and Games

Paper Accepted at the 14th ACM SIGGRAPH Conference on Motion, Interaction and Games

by Brandon Haworth | Sep 7, 2021 | Publications

In collaboration with GAIDG Lab external collaborators, York University PI Petros Faloutsos, PhD Student Melissa Kremer, and Master’s student Peter Caruana, and Rutgers University PI Mubbasir Kapadia, we develop a parametric pseudo-saliency map approach for speeding...
Paper Accepted at the International Symposium on Visual Computing (ISVC) 2021

Paper Accepted at the International Symposium on Visual Computing (ISVC) 2021

by Brandon Haworth | Sep 6, 2021 | Publications

GAIDG Lab member, recent graduate, and incoming Masters student (January 2021) has work accepted as a full conference paper on using Convolutional Neural Networks to identify Solfege hand signs in real-time directly from pixels on consumer-level webcams. The work will...
Student wins Jamie Cassels Undergraduate Research Award (JCURA) 2021-2022

Student wins Jamie Cassels Undergraduate Research Award (JCURA) 2021-2022

by Brandon Haworth | Aug 26, 2021 | Lab Member News

Undergraduate student Colin Johnson was awarded the Jamie Cassels Undergraduate Research Award (JCURA) 2021-2022 to work on vision and decision-making in navigation and signage accessibility with the GAIDG Lab.

Alumnus Awarded W.E. Cowie Innovation Award for work with GAIDG Lab

by Brandon Haworth | Aug 16, 2021 | Awards, Lab Member News

Recent alumnus, Yiping Wang, has been selected for the W.E. Cowie Innovation award for work on Unsupervised Environment Design to facilitate efficient and scalable Multi-Agent Reinforcement Learning by making summative assessments in a unique Teacher-Student paradigm....
Paper Accepted at ICML Workshop on Unsupervised Reinforcement Learning

Paper Accepted at ICML Workshop on Unsupervised Reinforcement Learning

by Brandon Haworth | Jul 5, 2021 | Publications

MASAI: Multi-agent Summative Assessment Improvement for Unsupervised Environment Design Reinforcement Learning agents require a distribution of environments for their policy to be trained on. The method or process of defining these environments directly impacts...
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GAIDG Lab
Department of Computer Science
Room 648, Engineering and Computer Science (ECS) Building
University of Victoria
Victoria, BC

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