The Drive&Act dataset is a state of the art multi modal benchmark for driver behavior recognition. The dataset includes 3D skeletons in addition to frame-wise hierarchical labels of 9.6 Million frames captured by 6 different views and 3 modalities (RGB, IR and depth).

It offers following key features:

  • 12h of video data in 29 long sequences
  • Calibrated multi view camera system with 5 views
  • Multi modal videos: NIR, Depth and Color data
  • Markerless motion capture: 3D Body Pose and Head Pose
  • Model of the static interior of the car
  • 83 manually annotated hierarchical activity labels:
    • Level 1: Long running tasks (12)
    • Level 2: Semantic actions (34)
    • Level 3: Object Interaction tripplets [action|object|location] (6|17|14)
Source: Drive&Act: A Multi-Modal Dataset for Fine-Grained Driver Behavior Recognition in Autonomous Vehicles


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