Memory Selection Network for Video Propagation

Ruizheng Wu; Huaijia Lin; Xiaojuan Qi; Jiaya Jia

doi:10.1007/978-3-030-58555-6_11

Memory Selection Network for Video Propagation

Ruizheng Wu^*, Huaijia Lin, Xiaojuan Qi, Jiaya Jia

^*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

11 Citations (Scopus)

Abstract

Video propagation is a fundamental problem in video processing where guidance frame predictions are propagated to guide predictions of the target frame. Previous research mainly treats the previous adjacent frame as guidance, which, however, could make the propagation vulnerable to occlusion, large motion and inaccurate information in the previous adjacent frame. To tackle this challenge, we propose a memory selection network, which learns to select suitable guidance from all previous frames for effective and robust propagation. Experimental results on video object segmentation and video colorization tasks show that our method consistently improves performance and can robustly handle challenging scenarios in video propagation.

Original language	English
Title of host publication	Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings
Editors	Andrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	175-190
Number of pages	16
ISBN (Print)	9783030585549
DOIs	https://doi.org/10.1007/978-3-030-58555-6_11
Publication status	Published - 2020
Externally published	Yes
Event	16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom Duration: 23 Aug 2020 → 28 Aug 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12360 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th European Conference on Computer Vision, ECCV 2020
Country/Territory	United Kingdom
City	Glasgow
Period	23/08/20 → 28/08/20

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Access to Document

10.1007/978-3-030-58555-6_11

Cite this

Wu, R., Lin, H., Qi, X., & Jia, J. (2020). Memory Selection Network for Video Propagation. In A. Vedaldi, H. Bischof, T. Brox, & J.-M. Frahm (Eds.), Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings (pp. 175-190). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12360 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58555-6_11

Wu, Ruizheng ; Lin, Huaijia ; Qi, Xiaojuan et al. / Memory Selection Network for Video Propagation. Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings. editor / Andrea Vedaldi ; Horst Bischof ; Thomas Brox ; Jan-Michael Frahm. Springer Science and Business Media Deutschland GmbH, 2020. pp. 175-190 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{09afd8868b5f4d218ebf93f662d72d33,

title = "Memory Selection Network for Video Propagation",

abstract = "Video propagation is a fundamental problem in video processing where guidance frame predictions are propagated to guide predictions of the target frame. Previous research mainly treats the previous adjacent frame as guidance, which, however, could make the propagation vulnerable to occlusion, large motion and inaccurate information in the previous adjacent frame. To tackle this challenge, we propose a memory selection network, which learns to select suitable guidance from all previous frames for effective and robust propagation. Experimental results on video object segmentation and video colorization tasks show that our method consistently improves performance and can robustly handle challenging scenarios in video propagation.",

author = "Ruizheng Wu and Huaijia Lin and Xiaojuan Qi and Jiaya Jia",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 16th European Conference on Computer Vision, ECCV 2020 ; Conference date: 23-08-2020 Through 28-08-2020",

year = "2020",

doi = "10.1007/978-3-030-58555-6\_11",

language = "English",

isbn = "9783030585549",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "175--190",

editor = "Andrea Vedaldi and Horst Bischof and Thomas Brox and Jan-Michael Frahm",

booktitle = "Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings",

}

Wu, R, Lin, H, Qi, X & Jia, J 2020, Memory Selection Network for Video Propagation. in A Vedaldi, H Bischof, T Brox & J-M Frahm (eds), Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12360 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 175-190, 16th European Conference on Computer Vision, ECCV 2020, Glasgow, United Kingdom, 23/08/20. https://doi.org/10.1007/978-3-030-58555-6_11

Memory Selection Network for Video Propagation. / Wu, Ruizheng; Lin, Huaijia; Qi, Xiaojuan et al.
Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings. ed. / Andrea Vedaldi; Horst Bischof; Thomas Brox; Jan-Michael Frahm. Springer Science and Business Media Deutschland GmbH, 2020. p. 175-190 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12360 LNCS).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Memory Selection Network for Video Propagation

AU - Wu, Ruizheng

AU - Lin, Huaijia

AU - Qi, Xiaojuan

AU - Jia, Jiaya

PY - 2020

Y1 - 2020

N2 - Video propagation is a fundamental problem in video processing where guidance frame predictions are propagated to guide predictions of the target frame. Previous research mainly treats the previous adjacent frame as guidance, which, however, could make the propagation vulnerable to occlusion, large motion and inaccurate information in the previous adjacent frame. To tackle this challenge, we propose a memory selection network, which learns to select suitable guidance from all previous frames for effective and robust propagation. Experimental results on video object segmentation and video colorization tasks show that our method consistently improves performance and can robustly handle challenging scenarios in video propagation.

AB - Video propagation is a fundamental problem in video processing where guidance frame predictions are propagated to guide predictions of the target frame. Previous research mainly treats the previous adjacent frame as guidance, which, however, could make the propagation vulnerable to occlusion, large motion and inaccurate information in the previous adjacent frame. To tackle this challenge, we propose a memory selection network, which learns to select suitable guidance from all previous frames for effective and robust propagation. Experimental results on video object segmentation and video colorization tasks show that our method consistently improves performance and can robustly handle challenging scenarios in video propagation.

UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001500594100011

UR - https://openalex.org/W3105065006

UR - https://www.scopus.com/pages/publications/85097363711

U2 - 10.1007/978-3-030-58555-6_11

DO - 10.1007/978-3-030-58555-6_11

M3 - Conference Paper published in a book

SN - 9783030585549

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 175

EP - 190

BT - Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings

A2 - Vedaldi, Andrea

A2 - Bischof, Horst

A2 - Brox, Thomas

A2 - Frahm, Jan-Michael

PB - Springer Science and Business Media Deutschland GmbH

T2 - 16th European Conference on Computer Vision, ECCV 2020

Y2 - 23 August 2020 through 28 August 2020

ER -

Wu R, Lin H, Qi X, Jia J. Memory Selection Network for Video Propagation. In Vedaldi A, Bischof H, Brox T, Frahm JM, editors, Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 175-190. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-58555-6_11

Memory Selection Network for Video Propagation

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