Datasets › AIR-Act2Act
AIR-Act2Act
AIR-Act2Act is a human-human interaction dataset for teaching non-verbal social behaviors to robots. It is different from other datasets because elderly people have participated in as performers. The authors recruited 100 elderly people and two college students to perform 10 interactions in an indoor environment. The entire dataset has 5,000 interaction samples, each of which contains depth maps, body indexes and 3D skeletal data that are captured with three Microsoft Kinect v2 cameras. In addition, the dataset also contains the joint angles of a humanoid NAO robot which are converted from the human behavior that robots need to learn.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 3 papers for it but never published that list.
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
Unknown
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- AIR-Act2Act
1 variant name, as the archive lists them.
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