KepSalinst : Using Peripheral Points to Delineate Salient Instances

Jinpeng CHEN, Runmin CONG, Horace Ho Shing IP, Sam KWONG

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

6 Citations (Scopus)

Abstract

Salient instance segmentation (SIS) is an emerging field that evolves from salient object detection (SOD), aiming at identifying individual salient instances using segmentation maps. Inspired by the success of dynamic convolutions in segmentation tasks, this article introduces a keypoints-based SIS network (KepSalinst). It employs multiple keypoints, that is, the center and several peripheral points of an instance, as effective geometrical guidance for dynamic convolutions. The features at peripheral points can help roughly delineate the spatial extent of the instance and complement the information inside the central features. To fully exploit the complementary components within these features, we design a differentiated patterns fusion (DPF) module. This ensures that the resulting dynamic convolutional filters formed by these features are sufficiently comprehensive for precise segmentation. Furthermore, we introduce a high-level semantic guided saliency (HSGS) module. This module enhances the perception of saliency by predicting a map for the input image to estimate a saliency score for each segmented instance. On four SIS datasets (ILSO, SOC, SIS10K, and COME15K), our KepSalinst outperforms all previous models qualitatively and quantitatively.
Original languageEnglish
Pages (from-to)3392-3405
Number of pages14
JournalIEEE Transactions on Cybernetics
Volume54
Issue number6
Early online date9 Nov 2023
DOIs
Publication statusPublished - 1 Jun 2024

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Funding

This work was supported in part by the National Key Research and Development Program of China under Grant 2021ZD0112100;in part by the Hong Kong Innovation and Technology Commission (InnoHK Project CIMDA); in part by the Hong Kong GRF-RGC General Research Fund under Grant 11209819 and Grant 11203820; in part by the National Natural Science Foundation of China under Grant 62002014; in part by the Taishan Scholar Project of Shandong Province under Grant tsqn202306079; in part by the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology under Grant 2020QNRC001; and in part by the CAAI-Huawei Mind Spore Open Fund.

Keywords

  • Dynamic convolution
  • Fuses
  • Head
  • Object detection
  • Remote sensing
  • Semantics
  • Task analysis
  • Urban areas
  • peripheral points
  • salient instance segmentation (SIS)

Fingerprint

Dive into the research topics of 'KepSalinst : Using Peripheral Points to Delineate Salient Instances'. Together they form a unique fingerprint.

Cite this