Dynamic Message Propagation Network for RGB-D and Video Salient Object Detection

Baian CHEN, Zhilei CHEN, Xiaowei HU, Jun XU, Haoran XIE*, Jing QIN, Mingqiang WEI*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

1 Citation (Scopus)

Abstract

Exploiting long-range semantic contexts and geometric information is crucial to infer salient objects from RGB and depth features. However, existing methods mainly focus on excavating local features within fixed regions by continuously feeding forward networks. In this article, we introduce Dynamic Message Propagation (DMP) to dynamically learn context information within more flexible regions. We integrate DMP into a Siamese-based network to process the RGB image and depth map separately and design a multi-level feature fusion module to explore cross-level information between refined RGB and depth features. Extensive experiments show clear improvements of our method over 17 methods on six benchmark datasets for RGB-D salient object detection (SOD). Additionally, our method outperforms its competitors for the video SOD task. Code is available at https://github.com/chenbaian-cs/DMPNet.

Original languageEnglish
Article number3597612
Number of pages21
JournalACM Transactions on Multimedia Computing, Communications and Applications
Volume20
Issue number1
Early online date19 May 2023
DOIs
Publication statusPublished - Jan 2024

Bibliographical note

Funding Information:
This work was supported by the Shenzhen Science and Technology Program (No. JCYJ20220818103401003, No. JCYJ20220530172403007), by the General Program of Natural Science Foundation of Guangdong Province (No. 2022A1515010170), by the Free Exploration of Basic Research Project, Local Science and Technology Development Fund Guided by the Central Government of China (No. 2021Szvup060), and the Research Grant entitled "Self-Supervised Learning for Medical Images"' (No. 871228) and Shenzhen University-Lingnan University Joint Research Programme (SZU-LU006/ 2122) of Lingnan University, Hong Kong.

Publisher Copyright:
© 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

Keywords

  • RGB-D salient object detection
  • dynamic message propagation
  • cross-modal learning
  • depth feature propagation

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