Scale AI is pleased to announce the launch of Sensor Fusion Segmentation - Scale’s endpoint for point cloud segmentation.
Released at CVPR 2019, Sensor Fusion Segmentation provides the highest precision for annotating complex objects that cannot be easily described with LiDAR cuboid labeling. Examples include vegetation, smoke/exhaust, splashes/puddles, rain and reflections.
Semantic scene understanding is important for a variety of applications, particularly autonomous driving. Rigorously tested by a handful of Scale’s customers during a private beta, Sensor Fusion Segmentation annotation provides fine-grained understanding of surfaces and objects in a 3D point cloud.
Take a look below, for how we helped the Toyota Research Institute (TRI) accelerate their research projects by giving them greater flexibility and the ability to amend workflows.
Since starting its work with Scale, TRI has been able to support four large annotation pipelines without significantly increasing the size of their team.