Zero-shot detection of buildings in mobile LiDAR using Language Vision Model

arXiv:2404.09931v1 Announce Type: new
Abstract: Recent advances have demonstrated that Language Vision Models (LVMs) surpass the existing State-of-the-Art (SOTA) in two-dimensional (2D) computer vision tasks, motivating attempts to apply LVMs to three-dimensional (3D) data. While LVMs are efficient and effective in addressing various downstream 2D vision tasks without training, they face significant challenges when it comes to point clouds, a representative format for representing 3D data. It is more difficult to extract features from 3D data and there are challenges …

abstract advances apply art arxiv buildings computer computer vision cs.ai cs.cv data detection language lidar mobile sota state tasks three-dimensional training type vision vision models zero-shot