A5056708225- Remote Sensing and LiDAR Applications
- 3D Shape Modeling and Analysis
- 3D Surveying and Cultural Heritage
- Radio Astronomy Observations and Technology
- Astronomical Observations and Instrumentation
Yantai University
2023-2024
China Electronics Technology Group Corporation
2017
In recent years, the abundance of information in 3D data has made semantic segmentation point clouds a topic great interest. However, current methods often rely solely on original three-dimensional coordinates cloud as input geometric features, leading to poor generalization performance. Additionally, occlusion can negatively impact accuracy when only local is considered. To address these issues, this paper proposes network named LGFF-Net. fully utilize clouds, we designed Local Feature...
Due to the influence of objective factors such as scene noise and hardware equipment, compared CAD modeling point clouds, real clouds collected by LiDAR often have strong non-uniformity irregularity, which leads low ability traditional cloud classification models extract features in scenes poor robustness. To address this issue, we added a local feature fusion module dense connected method PointMLP, thereby encoding broader information into features. The simple stacking multiple MLP Mixer...