This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …

This paper tries to give a gentle introduction to deep learning in medical image processing,
proceeding from theoretical foundations to applications. We first discuss general reasons for …

We present AIST++, a new multi-modal dataset of 3D dance motion and music, along with
FACT, a Full-Attention Cross-modal Transformer network for generating 3D dance motion …

In the semi-supervised skeleton-based action recognition task, obtaining more
discriminative information from both labeled and unlabeled data is a challenging problem …

Human pose forecasting is a complex structured-data sequence-modelling task, which has
received increasing attention, also due to numerous potential applications. Research has …

Learning the spatial-temporal structure of body movements is a fundamental problem for
character motion synthesis. In this work, we propose a novel neural network architecture …

Human movement is goal-directed and influenced by the spatial layout of the objects in the
scene. To plan future human motion, it is crucial to perceive the environment–imagine how …

In this work we present a novel, robust transition generation technique that can serve as a
new tool for 3D animators, based on adversarial recurrent neural networks. The system …

How can we animate 3D-characters from a movie script or move robots by simply telling
them what we would like them to do?" How unstructured and complex can we make a …

Background The study of human movement within sports biomechanics and rehabilitation
settings has made considerable progress over recent decades. However, developing a …