Implicit Guidance and Explicit Representation of Semantic Information in Points Cloud: A Survey

TL;DR

This survey reviews recent advances in the integration of semantic information into point clouds, highlighting implicit guidance and explicit representation, and discusses datasets, challenges, and future directions for semantic point cloud analysis.

Contribution

It provides a comprehensive overview of semantic integration in point clouds, including applications, datasets, and challenges, offering insights into future research directions.

Findings

Semantic information enhances point cloud analysis accuracy.

Dual roles of semantic info include implicit guidance and explicit representation.

Identifies key datasets and future challenges in semantic point cloud research.

Abstract

Point clouds, a prominent method of 3D representation, are extensively utilized across industries such as autonomous driving, surveying, electricity, architecture, and gaming, and have been rigorously investigated for their accuracy and resilience. The extraction of semantic information from scenes enhances both human understanding and machine perception. By integrating semantic information from two-dimensional scenes with three-dimensional point clouds, researchers aim to improve the precision and efficiency of various tasks. This paper provides a comprehensive review of the diverse applications and recent advancements in the integration of semantic information within point clouds. We explore the dual roles of semantic information in point clouds, encompassing both implicit guidance and explicit representation, across traditional and emerging tasks. Additionally, we offer a comparative analysis of publicly available datasets tailored to specific tasks and present notable observations. In conclusion, we discuss several challenges and potential issues that may arise in the future when fully utilizing semantic information in point clouds, providing our perspectives on these obstacles. The classified and organized articles related to semantic based point cloud tasks, and continuously followed up on relevant achievements in different fields, which can be accessed through https://github.com/Jasmine-tjy/Semantic-based-Point-Cloud-Tasks.