RESSCAL3D: Resolution Scalable 3D Semantic Segmentation of Point Clouds

arXiv:2404.06863v1 Announce Type: new
Abstract: While deep learning-based methods have demonstrated outstanding results in numerous domains, some important functionalities are missing. Resolution scalability is one of them. In this work, we introduce a novel architecture, dubbed RESSCAL3D, providing resolution-scalable 3D semantic segmentation of point clouds. In contrast to existing works, the proposed method does not require the whole point cloud to be available to start inference. Once a low-resolution version of the input point cloud is available, first semantic predictions …

abstract architecture arxiv contrast cs.cv deep learning domains novel resolution results scalability scalable segmentation semantic them type work