  The analysis of the ubiquitous human-human interactions is pivotal for
understanding humans as social beings. Existing human-human interaction
datasets typically suffer from inaccurate body motions, lack of hand gestures
and fine-grained textual descriptions. To better perceive and generate
human-human interactions, we propose Inter-X, a currently largest human-human
interaction dataset with accurate body movements and diverse interaction
patterns, together with detailed hand gestures. The dataset includes ~11K
interaction sequences and more than 8.1M frames. We also equip Inter-X with
versatile annotations of more than 34K fine-grained human part-level textual
descriptions, semantic interaction categories, interaction order, and the
relationship and personality of the subjects. Based on the elaborate
annotations, we propose a unified benchmark composed of 4 categories of
downstream tasks from both the perceptual and generative directions. Extensive
experiments and comprehensive analysis show that Inter-X serves as a testbed
for promoting the development of versatile human-human interaction analysis.
Our dataset and benchmark will be publicly available for research purposes.
