Exploring long-short-term context for point cloud semantic segmentation

Anan Du, Shuchao Pang, Xiaoshui Huang, Jian Zhang, Qiang Wu

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

Point cloud semantic segmentation attracts numerous attention following the success of the point-based convolution neural network. Due to the ambiguity of the point-based feature, many methods study on integrating contextual information to solve the ambiguous problem. However, the extracted context is severely limited to the small input blocks. Few prior works exploit contextual information beyond the blocks to capture long-range dependencies. To address this limitation, we propose a novel long-short-term context framework, which adopts a long-short-term feature bank to exploit both the local context within each block and the long-range context beyond the current task block. The proposed framework is flexible and easy to be combined with existing models, thereby enables existing models to capture the larger range context. Extensive experiments demonstrate that the proposed model achieves improved segmentation performance, and augmenting existing models with a long-short-term feature bank consistently increases the performance.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2755-2759
Number of pages5
ISBN (Electronic)9781728163956
DOIs
Publication statusPublished - 2020
Event2020 IEEE International Conference on Image Processing, ICIP 2020 - Virtual, Abu Dhabi, United Arab Emirates
Duration: 25 Sep 202028 Sep 2020

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2020-October
ISSN (Print)1522-4880
ISSN (Electronic)2381-8549

Conference

Conference2020 IEEE International Conference on Image Processing, ICIP 2020
CountryUnited Arab Emirates
CityVirtual, Abu Dhabi
Period25/09/2028/09/20

Keywords

  • long-short-term context
  • point cloud
  • semantic segmentation

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