189 citations · 683 across the 22 of their papers we have counts for
4 papers · 1 filter
Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models
Simon Alexanderson, Rajmund Nagy, Jonas Beskow +1
Diffusion models have experienced a surge of interest as highly expressive yet efficiently trainable probabilistic models. We show that these models are an excellent fit for synthe…
Generating coherent spontaneous speech and gesture from text
Simon Alexanderson, Éva Székely, Gustav Eje Henter +2
Embodied human communication encompasses both verbal (speech) and non-verbal information (e.g., gesture and head movements). Recent advances in machine learning have substantially…
MoGlow: Probabilistic and controllable motion synthesis using normalising flows
Gustav Eje Henter, Simon Alexanderson, Jonas Beskow
Data-driven modelling and synthesis of motion is an active research area with applications that include animation, games, and social robotics. This paper introduces a new class of…
A Neural Network Approach to Missing Marker Reconstruction in Human Motion Capture
Taras Kucherenko, Jonas Beskow, Hedvig Kjellström
Optical motion capture systems have become a widely used technology in various fields, such as augmented reality, robotics, movie production, etc. Such systems use a large number o…