Results 31 to 40 of about 7,018 (281)
SSPC-Net: Semi-supervised Semantic 3D Point Cloud Segmentation Network [PDF]
, 2021 Point cloud semantic segmentation is a crucial task in 3D scene understanding. Existing methods mainly focus on employing a large number of annotated labels for supervised semantic segmentation.
Yang, Jian +3 more
core +1 more source
YUTO SEMANTIC: A LARGE SCALE AERIAL LIDAR DATASET FOR SEMANTIC SEGMENTATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Creating virtual duplicates of the real world has garnered significant attention due to its applications in areas such as autonomous driving, urban planning, and urban mapping.
S. Yoo, C. Ko, G. Sohn, H. Lee
doaj +1 more source
Survey of Point Cloud Semantic Segmentation Based on Deep Learning
Jisuanji kexue yu tansuo, 2021 In recent years, the popularity of depth sensors and 3D laserscanners has led to a rapid development of 3D point clouds processing methods. Semantic segmentation of point cloud, as a key step in understanding 3D scenes, has attracted extensive attention ...
JING Zhuangwei, GUAN Haiyan, ZANG Yufu, NI Huan, LI Dilong, YU Yongtao
doaj +1 more source
2D TO 3D LABEL PROPAGATION FOR THE SEMANTIC SEGMENTATION OF HERITAGE BUILDING POINT CLOUDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 During the last decade, the use of semantic models of 3D buildings and structures kept growing, fostered in particular by the spread of Building Information Models (BIMs), becoming quite popular in several civil engineering and geomatics applications ...
E. Pellis +5 more
doaj +1 more source
SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Point clouds are useful in many applications like autonomous driving and robotics as they provide natural 3D information of the surrounding environments. While there are extensive research on 3D point clouds, scene understanding on 4D point clouds, a series of consecutive 3D point clouds frames, is an emerging topic and yet under-investigated.
Hanyu Shi 0002 +4 more
openaire +2 more sources
Active and incremental learning for semantic ALS point cloud segmentation [PDF]
, 2020 Supervised training of a deep neural network for semantic segmentation of point clouds requires a large amount of labelled data. Nowadays, it is easy to acquire a huge number of points with high density in large-scale areas using current LiDAR and ...
Lin, YAPING (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente)
core +1 more source
Associatively Segmenting Instances and Semantics in Point Clouds [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 A 3D point cloud describes the real scene precisely and intuitively.To date how to segment diversified elements in such an informative 3D scene is rarely discussed. In this paper, we first introduce a simple and flexible framework to segment instances and semantics in point clouds simultaneously. Then, we propose two approaches which make the two tasks
Xinlong Wang +4 more
openaire +2 more sources
SEGCloud: Semantic Segmentation of 3D Point Clouds [PDF]
2017 International Conference on 3D Vision (3DV), 2017 3D semantic scene labeling is fundamental to agents operating in the real world. In particular, labeling raw 3D point sets from sensors provides fine-grained semantics. Recent works leverage the capabilities of Neural Networks (NNs), but are limited to coarse voxel predictions and do not explicitly enforce global consistency.
Lyne P. Tchapmi +4 more
openaire +2 more sources
Novel Class Discovery for 3D Point Cloud Semantic Segmentation [PDF]
, 2023 Novel class discovery (NCD) for semantic segmentation is the task of learning a model that can segment unlabelled (novel) classes using only the supervision from labelled (base) classes.
Riz, Luigi +3 more
core +1 more source
Point Cloud Semantic Segmentation
CoRR, 2023 7 pages, 2 figures, 8 tables Language ...
openaire +2 more sources