20 citations · 74 across the 14 of their papers we have counts for
7 papers · 1 filter
The Ordinal Annotation Game: How Construct Abstraction Shapes Crowdsourced Consensus
Kosmas Pinitas
Inter-annotator disagreement in real-time affect annotation is widely treated as stochastic noise. We challenge this view by modelling ordinal annotation as an implicit game-theore…
Across-Game Engagement Modelling via Few-Shot Learning
Kosmas Pinitas, Konstantinos Makantasis, Georgios N. Yannakakis
Domain generalisation involves learning artificial intelligence (AI) models that can maintain high performance across diverse domains within a specific task. In video games, for in…
GameVibe: A Multimodal Affective Game Corpus
Matthew Barthet, Maria Kaselimi, Kosmas Pinitas +3
As online video and streaming platforms continue to grow, affective computing research has undergone a shift towards more complex studies involving multiple modalities. However, th…
Predicting Player Engagement in Tom Clancy's The Division 2: A Multimodal Approach via Pixels and Gamepad Actions
Kosmas Pinitas, David Renaudie, Mike Thomsen +4
This paper introduces a large scale multimodal corpus collected for the purpose of analysing and predicting player engagement in commercial-standard games. The corpus is solicited…
Knowing Your Annotator: Rapidly Testing the Reliability of Affect Annotation
Matthew Barthet, Chintan Trivedi, Kosmas Pinitas +4
The laborious and costly nature of affect annotation is a key detrimental factor for obtaining large scale corpora with valid and reliable affect labels. Motivated by the lack of t…
From the Lab to the Wild: Affect Modeling via Privileged Information
Konstantinos Makantasis, Kosmas Pinitas, Antonios Liapis +1
How can we reliably transfer affect models trained in controlled laboratory conditions (in-vitro) to uncontrolled real-world settings (in-vivo)? The information gap between in-vitr…
Supervised Contrastive Learning for Affect Modelling
Kosmas Pinitas, Konstantinos Makantasis, Antonios Liapis +1
Affect modeling is viewed, traditionally, as the process of mapping measurable affect manifestations from multiple modalities of user input to affect labels. That mapping is usuall…