Introducing Point Cloud Segmentation

byon June 24, 2019

Scale AI is pleased to announce the launch of Sensor Fusion Segmentation -

Scale’s endpoint for point cloud segmentation.

Sensor Fusion Viewer rendering a scene from nuScenes

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.

fog seen through LiDARFog

fog seen through LiDARSmoke/Exhaust

vegetation seen through LiDARVegetation

Trucks with open backs seen through LiDARTrucks with open backs

reflections seen through LiDARReflections

Splashes & Puddles seen through LiDARSplashes & Puddles

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


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.

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