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LiDAR Point Cloud Generation for SLAM Algorithm Evaluation [PDF]
Sensors, 2021 With the emerging interest in the autonomous driving level at 4 and 5 comes a necessity to provide accurate and versatile frameworks to evaluate the algorithms used in autonomous vehicles.
Łukasz Sobczak +3 more
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EPGNet: Enhanced Point Cloud Generation for 3D Object Detection [PDF]
Sensors, 2020 Three-dimensional object detection from point cloud data is becoming more and more significant, especially for autonomous driving applications. However, it is difficult for lidar to obtain the complete structure of an object in a real scene due to its ...
Qingsheng Chen +8 more
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Deep Auxiliary Learning for Point Cloud Generation [PDF]
IEEE Access, 2020 Generation point cloud from single image is a classical problem in computer vision. The learning methods for this task often adopt local distance metrics as loss function, which means the generated points are not easy to meet the overall shape ...
Fei Hu +4 more
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Point Cloud Adversarial Perturbation Generation for Adversarial Attacks
IEEE Access, 2023 In recent years, 3D model analysis has made a revolutionary development. Point cloud contains rich 3D object geometry information, which is an important 3D object data format widely used in many applications. However, the irregularity and disorder of the
Fengmei He +3 more
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Point cloud generation adversarial network based on self-attention and curvature. [PDF]
PLoS ONEAs a mainstream form of 3D data, point clouds are widely used in computer vision for tasks such as segmentation, classification, and target detection due to their simple representation method and high stability and accuracy.
Fusheng Sun +5 more
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View-Agnostic Point Cloud Generation for Occlusion Reduction in Aerial Lidar
Remote Sensing, 2022 Occlusions are one of the leading causes of data degradation in lidar. The presence of occlusions reduces the overall aesthetic quality of a point cloud, creating a signature that is specific to that viewpoint and sensor modality.
Nina Singer, Vijayan K. Asari
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Comparative Assessment of Neural Radiance Fields and 3D Gaussian Splatting for Point Cloud Generation from UAV Imagery [PDF]
SensorsPoint clouds continue to be the main data source in 3D modeling studies with unmanned aerial vehicle (UAV) images. Structure-from-Motion (SfM) and MultiView Stereo (MVS) have high time costs for point cloud generation, especially in large data sets.
Muhammed Enes Atik
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Remote SensingThe key to building a 3D point cloud map is to ensure the consistency and accuracy of point cloud data. However, the hardware limitations of LiDAR lead to a sparse and uneven distribution of point cloud data in the edge region, which brings many ...
Wenwen Li +5 more
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Sensors, 2012 The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems.
Tomi Rosnell, Eija Honkavaara
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STRATEGY ON HIGH-DEFINITION POINT CLOUD MAP CREATION FOR AUTONOMOUS DRIVING IN HIGHWAY ENVIRONMENTS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 In recent years, a lot of researchers have been trying the development of efficient ways to create HD maps with centimeter-level precision. Mobile mapping system (MMS) produce 3D HD point cloud map of the surrounding by integrating navigation (i.e ...
S. Srinara +5 more
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