Light Detection and Ranging
Light Detection and Ranging (LiDAR) is a remote sensing technology used to create detailed 3D maps by measuring distances using laser beams. Current research focuses on improving LiDAR data quality through techniques like super-resolution and denoising, often employing deep learning models such as Generative Adversarial Networks (GANs) and convolutional neural networks (CNNs), to enhance point cloud processing and object detection. These advancements are crucial for applications in autonomous vehicles, robotics, urban planning, and environmental monitoring, improving accuracy, efficiency, and robustness in challenging conditions.
Papers
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PCSCNet: Fast 3D Semantic Segmentation of LiDAR Point Cloud for Autonomous Car using Point Convolution and Sparse Convolution Network
Jaehyun Park, Chansoo Kim, Kichun Jo
LiDAR-guided Stereo Matching with a Spatial Consistency Constraint
Yongjun Zhang, Siyuan Zou, Xinyi Liu, Xu Huang, Yi Wan, Yongxiang Yao
January 29, 2022
January 27, 2022