no code implementations • 4 Feb 2020 • Miklas S. Kristoffersen, Sven E. Shepstone, Zheng-Hua Tan
This embedding space is used for exploring relevant content in various viewing settings by applying an N-pairs loss objective as well as a relaxed variant proposed in this paper.
no code implementations • 13 Sep 2019 • Miklas S. Kristoffersen, Jacob L. Wieland, Sven E. Shepstone, Zheng-Hua Tan, Vinoba Vinayagamoorthy
This paper proposes a deep learning-based method for learning joint context-content embeddings (JCCE) with a view to context-aware recommendations, and demonstrate its application in the television domain.
no code implementations • 12 Dec 2018 • Andrea Coifman, Péter Rohoska, Miklas S. Kristoffersen, Sven E. Shepstone, Zheng-Hua Tan
Attention level estimation systems have a high potential in many use cases, such as human-robot interaction, driver modeling and smart home systems, since being able to measure a person's attention level opens the possibility to natural interaction between humans and computers.
no code implementations • 30 Jul 2018 • Miklas S. Kristoffersen, Sven E. Shepstone, Zheng-Hua Tan
Home entertainment systems feature in a variety of usage scenarios with one or more simultaneous users, for whom the complexity of choosing media to consume has increased rapidly over the last decade.