中文版 | English
Title

Video Object Segmentation using Point-based Memory Network

Author
Corresponding AuthorHan,Jungong
Publication Years
2023-02-01
DOI
Source Title
ISSN
0031-3203
EISSN
1873-5142
Volume134
Abstract
Recent years have witnessed the prevalence of memory-based methods for Semi-supervised Video Object Segmentation (SVOS) which utilise past frames efficiently for label propagation. When conducting feature matching, fine-grained multi-scale feature matching has typically been performed using all query points, which inevitably results in redundant computations and thus makes the fusion of multi-scale results ineffective. In this paper, we develop a new Point-based Memory Network, termed as PMNet, to perform fine-grained feature matching on hard samples only, assuming that easy samples can already obtain satisfactory matching results without the need for complicated multi-scale feature matching. Our approach first generates an uncertainty map from the initial decoding outputs. Next, the fine-grained features at uncertain locations are sampled to match the memory features on the same scale. Finally, the matching results are further decoded to provide a refined output. The point-based scheme works with the coarsest feature matching in a complementary and efficient manner. Furthermore, we propose an approach to adaptively perform global or regional matching based on the motion history of memory points, making our method more robust against ambiguous backgrounds. Experimental results on several benchmark datasets demonstrate the superiority of our proposed method over state-of-the-art methods.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
First
WOS Research Area
Computer Science ; Engineering
WOS Subject
Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS Accession No
WOS:000927839900004
Publisher
ESI Research Field
ENGINEERING
Scopus EID
2-s2.0-85139349829
Data Source
Scopus
Citation statistics
Cited Times [WOS]:1
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/406144
DepartmentDepartment of Computer Science and Engineering
Affiliation
1.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
2.WMG Data Science,University of Warwick,Coventry,CV4 7AL,United Kingdom
3.Department of Computer Science,Aberystwyth University,Aberystwyth,SY23 3DB,United Kingdom
First Author AffilicationDepartment of Computer Science and Engineering
First Author's First AffilicationDepartment of Computer Science and Engineering
Recommended Citation
GB/T 7714
Gao,Mingqi,Han,Jungong,Zheng,Feng,et al. Video Object Segmentation using Point-based Memory Network[J]. PATTERN RECOGNITION,2023,134.
APA
Gao,Mingqi,Han,Jungong,Zheng,Feng,Yu,James J.Q.,&Montana,Giovanni.(2023).Video Object Segmentation using Point-based Memory Network.PATTERN RECOGNITION,134.
MLA
Gao,Mingqi,et al."Video Object Segmentation using Point-based Memory Network".PATTERN RECOGNITION 134(2023).
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