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Unsupervised point cloud representation learning with deep neural networks: A survey
Point cloud data have been widely explored due to its superior accuracy and robustness
under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved …
under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved …
Semantic segmentation of 3d lidar data using deep learning: a review of projection-based methods
LiDAR sensor is an active remote sensing sensor that is increasingly used to capture 3D
information of real-world objects. Real-time decision-making applications such as …
information of real-world objects. Real-time decision-making applications such as …
Polarmix: A general data augmentation technique for lidar point clouds
LiDAR point clouds, which are usually scanned by rotating LiDAR sensors continuously,
capture precise geometry of the surrounding environment and are crucial to many …
capture precise geometry of the surrounding environment and are crucial to many …
3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds
Robust point cloud parsing under all-weather conditions is crucial to level-5 autonomy in
autonomous driving. However, how to learn a universal 3D semantic segmentation (3DSS) …
autonomous driving. However, how to learn a universal 3D semantic segmentation (3DSS) …
Transfer learning from synthetic to real lidar point cloud for semantic segmentation
Abstract Knowledge transfer from synthetic to real data has been widely studied to mitigate
data annotation constraints in various computer vision tasks such as semantic segmentation …
data annotation constraints in various computer vision tasks such as semantic segmentation …
PCSCNet: Fast 3D semantic segmentation of LiDAR point cloud for autonomous car using point convolution and sparse convolution network
The autonomous car must recognize the driving environment quickly for safe driving. As the
Light Detection And Range (LiDAR) sensor is widely used in the autonomous car, fast …
Light Detection And Range (LiDAR) sensor is widely used in the autonomous car, fast …
SwinURNet: Hybrid transformer-cnn architecture for real-time unstructured road segmentation
Semantic segmentation is a crucial component of autonomous driving. However, the
segmentation performance in unstructured roads is challenging owing to the following …
segmentation performance in unstructured roads is challenging owing to the following …
TransRVNet: LiDAR semantic segmentation with transformer
Effective and efficient 3D semantic segmentation from large-scale LiDAR point cloud is a
fundamental problem in the field of autonomous driving. In this paper, we present …
fundamental problem in the field of autonomous driving. In this paper, we present …
A survey of label-efficient deep learning for 3d point clouds
In the past decade, deep neural networks have achieved significant progress in point cloud
learning. However, collecting large-scale precisely-annotated point clouds is extremely …
learning. However, collecting large-scale precisely-annotated point clouds is extremely …
Adversarial point cloud perturbations against 3D object detection in autonomous driving systems
Deep learning models have been demonstrated vulnerable to adversarial attacks even with
imperceptible perturbations. As such, the reliability of existing deep neural networks-based …
imperceptible perturbations. As such, the reliability of existing deep neural networks-based …