Abstract: Point cloud completion, which involves inferring missing regions of 3D objects from partial observations, remains a challenging problem in 3D vision and robotics. Existing learning-based ...
Abstract: With the popularity of mobile devices and the increasing demand for indoor localization services, the localization of indoor mobile users is becoming more and more popular. However, many ...
Abstract: Multispectral LiDAR contributes to the rapid acquisition of 3D spatial and spectral information of land covers, providing more comprehensive features for classification. Despite the ...
Abstract: Kernel point convolution (KPConv) defines convolutional weights based on Euclidean distances between kernel points and input points and has shown good segmentation results on several ...