  In this paper, we present Motion-X, a large-scale 3D expressive whole-body
motion dataset. Existing motion datasets predominantly contain body-only poses,
lacking facial expressions, hand gestures, and fine-grained pose descriptions.
Moreover, they are primarily collected from limited laboratory scenes with
textual descriptions manually labeled, which greatly limits their scalability.
To overcome these limitations, we develop a whole-body motion and text
annotation pipeline, which can automatically annotate motion from either
single- or multi-view videos and provide comprehensive semantic labels for each
video and fine-grained whole-body pose descriptions for each frame. This
pipeline is of high precision, cost-effective, and scalable for further
research. Based on it, we construct Motion-X, which comprises 15.6M precise 3D
whole-body pose annotations (i.e., SMPL-X) covering 81.1K motion sequences from
massive scenes. Besides, Motion-X provides 15.6M frame-level whole-body pose
descriptions and 81.1K sequence-level semantic labels. Comprehensive
experiments demonstrate the accuracy of the annotation pipeline and the
significant benefit of Motion-X in enhancing expressive, diverse, and natural
motion generation, as well as 3D whole-body human mesh recovery.
