  We address the problem of accurate capture and expressive modelling of
interactive behaviors happening between two persons in daily scenarios.
Different from previous works which either only consider one person or focus on
conversational gestures, we propose to simultaneously model the activities of
two persons, and target objective-driven, dynamic, and coherent interactions
which often span long duration. To this end, we capture a new dataset dubbed
InterAct, which is composed of 241 motion sequences where two persons perform a
realistic scenario over the whole sequence. The audios, body motions, and
facial expressions of both persons are all captured in our dataset. We also
demonstrate the first diffusion model based approach that directly estimates
the interactive motions between two persons from their audios alone. All the
data and code will be available at: https://hku-cg.github.io/interact.
