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Drive&Act dataset
A Multi-modal Dataset for Driver Behavior Recognition in Autonomous Vehicles
The Drive&Act dataset is a state of the art multi modal benchmark for action recognition in automated vehicles. 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)
Karlsruhe Institute of Technology (KIT)
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Task
Autonomous Driving
Annotation Types
Bounding Boxes
83
Items
400
Classes
83
Labels
Models using this dataset
Last updated on
January 20, 2022
Licensed under
Research Only
