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AAAI 2022

MBGRLp: Multiscale Bootstrap Graph Representation Learning on Pointcloud (Student Abstract)

Short Paper AAAI Student Abstract and Poster Program Artificial Intelligence

Abstract

Point cloud has gained a lot of attention with the availability of large amount of point cloud data and increasing applications like city planning and self-driving cars. However, current methods, often rely on labeled information and costly processing, such as converting point cloud to voxel. We propose a self-supervised learning approach to tackle these problems, combating labelling and additional memory cost issues. Our proposed method achieves results comparable to supervised and unsupervised baselines on widely used benchmark datasets for self-supervised point cloud classification like ShapeNet, ModelNet10/40.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
260957147423323383