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.