3D Point Cloud Task types
Note
After careful consideration, we have made the decision to close new customer access to AWS Ground Truth, effective 7/30/26. Existing customers can continue to use the service as normal. AWS continues to invest in security and availability improvements for Ground Truth, but we do not plan to introduce new features.
You can use Ground Truth 3D point cloud labeling modality for a variety of use cases. The following list briefly describes each 3D point cloud task type. For additional details and instructions on how to create a labeling job using a specific task type, select the task type name to see its task type page.
-
3D point cloud object detection – Use this task type when you want workers to locate and classify objects in a 3D point cloud by adding and fitting 3D cuboids around objects.
-
3D point cloud object tracking – Use this task type when you want workers to add and fit 3D cuboids around objects to track their movement across a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
-
3D point cloud semantic segmentation – Use this task type when you want workers to create a point-level semantic segmentation mask by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
-
3D point cloud adjustment task types – Each of the task types above has an associated adjustment task type that you can use to audit and adjust annotations generated from a 3D point cloud labeling job. Refer to the task type page of the associated type to learn how to create an adjustment labeling job for that task.
