Deep learning for lidar point clouds in autonomous driving: A review
Recently, the advancement of deep learning (DL) in discriminative feature learning from 3-D
LiDAR data has led to rapid development in the field of autonomous driving. However …
LiDAR data has led to rapid development in the field of autonomous driving. However …
Neural implicit embedding for point cloud analysis
K Fujiwara, T Hashimoto - … of the IEEE/CVF conference on …, 2020 - openaccess.thecvf.com
We present a novel representation for point clouds that encapsulates the local
characteristics of the underlying structure. The key idea is to embed an implicit …
characteristics of the underlying structure. The key idea is to embed an implicit …
IPD-Net: SO (3) Invariant Primitive Decompositional Network for 3D Point Clouds
In this paper, we propose IPD-Net: Invariant Primitive Decompositional Network, a SO (3)
invariant framework for decomposition of a point cloud. The human cognitive system is able …
invariant framework for decomposition of a point cloud. The human cognitive system is able …
Deep Learning for 3D Information Extraction from Indoor and Outdoor Point Clouds
Y Li - 2021 - uwspace.uwaterloo.ca
This thesis focuses on the challenges and opportunities that come with deep learning in the
extraction of 3D information from point clouds. To achieve this, 3D information such as point …
extraction of 3D information from point clouds. To achieve this, 3D information such as point …