This paper provides the EVOPS dataset for plane segmentation from 3D data, both from RGBD images and LiDAR point clouds. We have designed two annotation methodologies (RGBD and LiDAR) running on well-known and widely-used datasets for SLAM evaluation and we have provided a complete set of benchmarking tools including point, planes and segmentation metrics. The data includes a total number of 10k RGBD and 7K LiDAR frames over different selected scenes which consist of high quality segmented planes. The experiments report quality of SOTA methods for RGBD plane segmentation on our annotated data. We also have provided learnable baseline for plane segmentation in LiDAR point clouds. All labeled data and benchmark tools used have been made publicly available at https://evops.netlify.app/.
@article{arxiv.2204.05799,
title = {EVOPS Benchmark: Evaluation of Plane Segmentation from RGBD and LiDAR Data},
author = {Anastasiia Kornilova and Dmitrii Iarosh and Denis Kukushkin and Nikolai Goncharov and Pavel Mokeev and Arthur Saliou and Gonzalo Ferrer},
journal= {arXiv preprint arXiv:2204.05799},
year = {2022}
}