ADL4D: Towards A Contextually Rich Dataset for 4D Activities of Daily Living

Understand

Hand-Object Interactions (HOIs) are conditioned on spatial and temporal contexts like surrounding objects, previous actions, and future intents (for example, grasping and handover actions vary greatly based on objects proximity and trajectory obstruction).

• However, existing datasets for 4D HOI (3D HOI over time) are limited to one subject interacting with one object only.
• This restricts the generalization of learning-based HOI methods trained on those datasets.
• We introduce ADL4D, a dataset of up to two subjects interacting with different sets of objects performing Activities of Daily Living (ADL) like breakfast or lunch preparation activities.