Fig. 1. Overview of 3D-TAL, LocATe, and BT-ALL.

a 3D-TAL Task Description: 3D Temporal Action Localization (3D-TAL) involves identifying actions and their precise spans (start and end times) in a 3D motion sequence. We compare the human-provided labels for the 3D motion with predictions from our proposed LocATe approach. Predictions from LocATe correlate well with human labels, including simultaneous actions (visualized as temporal overlaps between different action spans). LocATe produces accurate localizations, and meaningful actions (even when disagreeing with the human label, e.g., “Grasp Something” vs. “Bend''). b LocATe Framework: Given a sequence of human poses, LocATe outputs a set of action spans via an encoding-decoding paradigm. c Class frequency distributions of the introduced BABEL-TAL-ALL (BT-ALL): This dataset offers a rich spectrum of action labels and demonstrates intra-class diversity. Additionally, the distribution of action data closely follows a long-tailed pattern, mirroring real-world scenarios.