Name:
Thabet_Self-Supervised_Learning_of_Local_Features_in_3D_Point_Clouds_CVPRW_2020_paper.pdf
Size:
679.8Kb
Format:
PDF
Description:
CVF Open Access version
Type
Conference PaperKAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
VCC Analytics Research Group
Visual Computing Center (VCC)
Date
2020-07-28Online Publication Date
2020-07-28Print Publication Date
2020-06Permanent link to this record
http://hdl.handle.net/10754/664502
Metadata
Show full item recordAbstract
We present a self-supervised task on point clouds, in order to learn meaningful point-wise features that encode local structure around each point. Our self-supervised network, operates directly on unstructured/unordered point clouds. Using a multi-layer RNN, our architecture predicts the next point in a point sequence created by a popular and fast Space Filling Curve, the Morton-order curve. The final RNN state (coined Morton feature) is versatile and can be used in generic 3D tasks on point clouds. Our experiments show how our self-supervised task results in features that are useful for 3D segmentation tasks, and generalize well between datasets. We show how Morton features can be used to significantly improve performance (+3% for 2 popular algorithms) in semantic segmentation of point clouds on the challenging and large-scale S3DIS dataset. We also show how our self-supervised network pretrained on S3DIS transfers well to another large-scale dataset, vKITTI, leading to 11% improvement. Our code is publicly available.1Citation
Thabet, A., Alwassel, H., & Ghanem, B. (2020). Self-Supervised Learning of Local Features in 3D Point Clouds. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). doi:10.1109/cvprw50498.2020.00477Conference/Event name
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)ISBN
978-1-7281-9361-8Additional Links
https://ieeexplore.ieee.org/document/9150706/https://ieeexplore.ieee.org/document/9150706/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9150706
https://openaccess.thecvf.com/content_CVPRW_2020/papers/w54/Thabet_Self-Supervised_Learning_of_Local_Features_in_3D_Point_Clouds_CVPRW_2020_paper.pdf
ae974a485f413a2113503eed53cd6c53
10.1109/CVPRW50498.2020.00477