Christian Thurau

TL;DR: This work describes the ongoing collection of the “something-something” database of video prediction tasks whose solutions require a common sense understanding of the depicted situation, and describes the challenges in crowd-sourcing this data at scale.

TL;DR: This paper presents a method for recognizing human actions based on pose primitives that does not rely on background subtraction or dynamic features and thus allows for action recognition in still images.

TL;DR: In this paper, the authors presented case studies focusing on clustering analysis applied to high-dimensionality player behavior telemetry, covering a combined total of 260,000 characters from two major commercial game titles: the Massively Multiplayer Online Role-Playing Game Tera and the multi-player strategy war game Battlefield 2: Bad Company 2.

TL;DR: This paper presents the first cross-game study of churn prediction in Free-to-Play games, and develops a broadly applicable churn prediction model, which does not rely on game-design specific features.

TL;DR: This work applies for the first time a recent matrix factorisation technique, simplex volume maximisation (SiVM), to hyperspectral data, an unsupervised classification approach, optimised for fast computation of massive datasets.