From CAD Models to Soft Point Cloud Labels: An Automatic Annotation Pipeline for Cheaply Supervised 3D Semantic Segmentation

From CAD Models to Soft Point Cloud Labels: An Automatic Annotation Pipeline for Cheaply Supervised 3D Semantic Segmentation

We propose a fully automatic annotation scheme that takes a raw 3D point cloud with a set of fitted CAD models as input and outputs convincing point-wise labels that can be used as cheap training data for point cloud segmentation. Compared with manual annotations, we show that our automatic labels a...

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Bibliographic Details
Main Authors: Galadrielle Humblot-Renaux, Simon Buus Jensen, Andreas Møgelmose
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Remote Sensing
Subjects:
3D semantic segmentation
automatic labeling
soft labels
point clouds
deep learning
Online Access:https://www.mdpi.com/2072-4292/15/14/3578

Internet

https://www.mdpi.com/2072-4292/15/14/3578

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