Deep learning for 3d point clouds: A survey
Point cloud learning has lately attracted increasing attention due to its wide applications in
many areas, such as computer vision, autonomous driving, and robotics. As a dominating …
many areas, such as computer vision, autonomous driving, and robotics. As a dominating …
Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data
Deep learning techniques for point cloud data have demonstrated great potentials in solving
classical problems in 3D computer vision such as 3D object classification and segmentation …
classical problems in 3D computer vision such as 3D object classification and segmentation …
Ppf-foldnet: Unsupervised learning of rotation invariant 3d local descriptors
We present PPF-FoldNet for unsupervised learning of 3D local descriptors on pure point
cloud geometry. Based on the folding-based auto-encoding of well known point pair …
cloud geometry. Based on the folding-based auto-encoding of well known point pair …
Semantics for robotic map**, perception and interaction: A survey
For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …
require a deeper understanding of the world in which they operate. In robotics and related …
Deep learning based code smell detection
H Liu, J **, Z Xu, Y Zou, Y Bu… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Code smells are structures in the source code that suggest the possibility of refactorings.
Consequently, developers may identify refactoring opportunities by detecting code smells …
Consequently, developers may identify refactoring opportunities by detecting code smells …
Deep learning based feature envy detection
H Liu, Z Xu, Y Zou - Proceedings of the 33rd ACM/IEEE international …, 2018 - dl.acm.org
Software refactoring is widely employed to improve software quality. A key step in software
refactoring is to identify which part of the software should be refactored. To facilitate the …
refactoring is to identify which part of the software should be refactored. To facilitate the …
3d reconstruction and segmentation system for pavement potholes based on improved structure-from-motion (sfm) and deep learning
N Wang, J Dong, H Fang, B Li, K Zhai, D Ma… - … and Building Materials, 2023 - Elsevier
Traditional pothole detection based on two-dimensional images lacks three-dimensional
(3D) quantitative information such as depth and volume, although the high accuracy. In …
(3D) quantitative information such as depth and volume, although the high accuracy. In …
3D Lidar Point Cloud Segmentation for Automated Driving
The use of 3D point clouds (3DPCs) in deep learning (DL) has recently gained popularity
due to several applications in fields such as computer vision, autonomous systems, and …
due to several applications in fields such as computer vision, autonomous systems, and …
Semantic segmentation of large-scale point clouds based on dilated nearest neighbors graph
Abstract Three-dimensional (3D) semantic segmentation of point clouds is important in many
scenarios, such as automatic driving, robotic navigation, while edge computing is …
scenarios, such as automatic driving, robotic navigation, while edge computing is …
A fast point cloud recognition algorithm based on keypoint pair feature
Z Ge, X Shen, Q Gao, H Sun, X Tang, Q Cai - Sensors, 2022 - mdpi.com
At present, PPF-based point cloud recognition algorithms can perform better matching than
competitors and be verified in the case of severe occlusion and stacking. However, including …
competitors and be verified in the case of severe occlusion and stacking. However, including …