TULIP: Transformer for Upsampling of LiDAR Point Clouds
LiDAR Upsampling is a challenging task for the perception systems of robots and
autonomous vehicles due to the sparse and irregular structure of large-scale scene contexts …
autonomous vehicles due to the sparse and irregular structure of large-scale scene contexts …
Outdoor large-scene 3D point cloud reconstruction based on transformer
F Tang, S Zhang, B Zhu, J Sun - Frontiers in Physics, 2024 - frontiersin.org
3D point clouds collected by low-channel light detection and ranging (LiDAR) are relatively
sparse compared to high-channel LiDAR, which is considered costly. To address this, an …
sparse compared to high-channel LiDAR, which is considered costly. To address this, an …
TSE-UNet: Temporal and Spatial Feature-Enhanced Point Cloud Super-Resolution Model for Mechanical LiDAR
L Ren, D Li, Z Ouyang, Z Zhang - Applied Sciences, 2024 - mdpi.com
The mechanical LiDAR sensor is crucial in autonomous vehicles. After projecting a 3D point
cloud onto a 2D plane and employing a deep learning model for computation, accurate …
cloud onto a 2D plane and employing a deep learning model for computation, accurate …
Implicit Point Function for LiDAR Super-Resolution in Autonomous Driving
LiDAR super-resolution is a relatively new problem in which we seek to fill in the blanks
between measured points when a low-resolution LiDAR is given, making a high-resolution …
between measured points when a low-resolution LiDAR is given, making a high-resolution …