Login / Signup
LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Net.
Pierre Biasutti
Vincent Lepetit
Jean-François Aujol
Mathieu Brédif
Aurélie Bugeau
Published in:
ICCV Workshops (2019)
Keyphrases
</>
end to end
point cloud
semantic segmentation
congestion control
laser scanner
structure from motion
point sets
superpixels
image features
feature extraction
point cloud data
single image
image data
feature vectors
feature space
point correspondences
object detection
image processing
feature selection