The road to success is paved with consistent labeled data
Best-in-class driving intelligence for autonomous vehicles means refusing to compromise data labeling accuracy. From identifying static obstacles like traffic signs to tracking dynamic elements like pedestrians, precise labeling ensures your vehicle navigates with heightened autonomy and safety, even in the most challenging moments.
In the bustling city streets or on an erratic off-road path, assure continuous object tracking across all sensors and sequences. For instance, an object labeled with a 3D cuboid in a lidar’s point cloud can maintain its ID in the imagery across cameras.
Persistent object ID: Equip your autonomous vehicle with the capability to maintain consistent identification, whether interpreting 3D lidar data or 2D image sequences.
Maximized efficiency: Save valuable development time with reduced reconciliation and heightened model precision.
Occlusion management: Ensure continuous tracking by skillfully managing occlusions and maintaining object identification even during interruptions.
Fast-track your data labeling even in the most complex urban and off-road scenarios.
Effortless labeling: Transition from 3D to 2D data in a single click, receiving pre-labeled datasets requiring only minor refinements.
Flexible exporting: Instance, semantic or panoptic? Export your data in multiple formats depending on your needs.
Elevate your autonomous vehicle’s environmental understanding and navigate safely.
Enriched labeling context: Merge 2D and 3D sensor data, simplifying object differentiation and enhancing labeling precision.
Efficient labeling: Ensure labeling consistency by making sure a single annotator handles both the 3D and 2D data for a single sequence.
Accurate object classification: Facilitate swift, accurate object recognition, ensuring correct object classification for your project.
Label all your sensor’s data in one interface
Label fast, accurate and efficiently with ML-assisted features build for and by machine learning teams.
