Two-Person Interaction Augmentation with Skeleton Priors

arXiv:2404.05490v1 Announce Type: new
Abstract: Close and continuous interaction with rich contacts is a crucial aspect of human activities (e.g. hugging, dancing) and of interest in many domains like activity recognition, motion prediction, character animation, etc. However, acquiring such skeletal motion is challenging. While direct motion capture is expensive and slow, motion editing/generation is also non-trivial, as complex contact patterns with topological and geometric constraints have to be retained. To this end, we propose a new deep learning method for …

abstract animation arxiv augmentation continuous cs.cv dancing domains editing etc however human motion capture person prediction recognition type