RI Seminar: Gustav Eje Henter : Move over, MSE! – New probabilistic models of motion

Gustav Eje Henter Assistant Professor in Intelligent Systems with spec. in Machine Learning School of Electrical Engineering & Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden Friday, March 5, 2021 Abstract: Data-driven character animation holds great promise for games, film, virtual avatars and social robots. A “virtual AI actor” that moves in response to intuitive, high-level input could turn 3D animators into directors, instead of requiring them to laboriously pose the character for each frame of animation, as is the case today. However, the high bar on visual quality for most character-animation applications has hitherto constrained machine learning to narrow, task-specific solutions, rife with loss-function engineering and custom processing steps, in order to avoid artefacts such as foot sliding and regression to the mean. This talk makes the case that machine learning now has a