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Cited by 257Advanced Neural Network ApplicationsVideo Surveillance and Tracking MethodsVisual Attention and Saliency Detection

Collaborative Video Object Segmentation by Foreground-Background Integration

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Yang, Zongxin, Wei, Yunchao, Yang, Yi·2020·Lecture Notes in Computer Science
DOI 10.1007/978-3-030-58558-7_20
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  • Adopting a memory architecture to store object information from past frames is indispensable for accurately tracking objects in video.

    “To address the above challenges, adopting a memory architecture to store the object information from past frames is indispensable for accurately tracking objects in video [5,7,10,29,40,52,56,57,64,66,68].”

    From SAM2LONG: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree (2025) · cites this paper as [66]

    The paper describes a memory network as a feature of STMVOS (Related Work, p. 3), but does not say that such an architecture is indispensable. Instead, it describes CFBI as matching information from the first and previous frames (Related Work, p. 4) and reports that CFBI outperforms other state-of-the-art methods on three benchmarks (Introduction, p. 3). (LLM, conf=0.84)

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Research works printed but not linked: 38

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Cited by

Sorted by citations

Authors
Yang, Z., Wei, Y., & Yang, Y.
Affiliations
University of Technology Sydney (AU)
Corresponding author
Yang, Yi
ORCID
Venue
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Published
2020
Pages
332-348
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
DOI
10.1007/978-3-030-58558-7_20
OpenAlex
W3094664776
Cited by
257
References
5
Citations by year
2026: 7 · 2025: 29 · 2024: 58 · 2023: 63 · 2022: 54 · 2021: 38 · 2020: 8
FWCI
12.57
Type
conference paper
Language
en
Open access
Licence
Locations
  • Lecture notes in computer science (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • UTS ePRESS (University of Technology Sydney) (submittedVersion, other-oa)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
Keywords
video object segmentation, semi-supervised segmentation, feature embedding

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