SEMANTIC3D.NET: A NEW LARGE-SCALE POINT CLOUD CLASSIFICATION BENCHMARK
This paper presents a new 3D point cloud classification benchmark data set with over four billion manually labelled points, meant as input for data-hungry (deep) learning methods. We also discuss first submissions to the benchmark that use deep convolutional neural networks (CNNs) as a work horse,...
Main Authors: | T. Hackel, N. Savinov, L. Ladicky, J. D. Wegner, K. Schindler, M. Pollefeys |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-05-01
|
Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-1-W1/91/2017/isprs-annals-IV-1-W1-91-2017.pdf |
Similar Items
-
DNet: Dynamic Neighborhood Feature Learning in Point Cloud
by: Fujing Tian, et al.
Published: (2021-03-01) -
A BENCHMARK FOR LARGE-SCALE HERITAGE POINT CLOUD SEMANTIC SEGMENTATION
by: F. Matrone, et al.
Published: (2020-08-01) -
FAST SEMANTIC SEGMENTATION OF 3D POINT CLOUDS WITH STRONGLY VARYING DENSITY
by: T. Hackel, et al.
Published: (2016-06-01) -
DNET AS CAUSE OF SYMPTOMATIC EPILEPSY
by: Adina Roceanu, et al.
Published: (2011-03-01) -
CSPC-Dataset: New LiDAR Point Cloud Dataset and Benchmark for Large-Scale Scene Semantic Segmentation
by: Guofeng Tong, et al.
Published: (2020-01-01)