Jun 21, 2022 · To solve these problems, we propose a fast and lite point cloud semantic segmentation network for autonomous driving, which utilizes LiDAR ...
Aug 1, 2022 · We proposed a lite point cloud semantic segmentation for autonomous driving using synthetic LiDAR data. We sug- gested two methods for ...
In this paper, we propose the fast voxel-based semantic segmentation model using Point Convolution and 3D Sparse Convolution (PCSCNet).
RangeNet++: Fast and Accurate LiDAR Semantic Segmentation ... Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle Perception [link] ...
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Feb 21, 2022 · In this paper, we propose the fast voxel-based semantic segmentation model us- ing Point Convolution and 3D Sparse Convolution (PCSCNet). The ...
This paper introduces a deep encoder-decoder network, named SalsaNet, for efficient semantic segmentation of 3D LiDar point clouds, and introduces an ...
In this study, a lightweight CNN structure was proposed for projection-based LiDAR point cloud semantic segmentation with only 1.9 M parameters that gave an 87% ...
Missing: Synthetic | Show results with:Synthetic
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What is semantic segmentation for self driving cars?
What is the point cloud in autonomous driving?
To meet the accuracy and speed of LiDAR point clouds semantic segmentation, an efficient model ACPNet is proposed in this paper.
Missing: Synthetic | Show results with:Synthetic
It is entirely possible to increase lidar point cloud segmentation accuracy by supplementing the training process with generated synthetic data.
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Jan 24, 2024 · In contrast, projection-based methods are lightweight and fast, so real-time effects can be achieved during deployment. In terms of segmentation ...
Missing: Synthetic | Show results with:Synthetic