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Title: Guided Co-segmentation network for fast video object segmentation
Authors: Liu, Weide
Lin, Guosheng
Zhang, Tianyi
Liu, Zichuan
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Source: Liu, W., Lin, G., Zhang, T. & Liu, Z. (2021). Guided Co-segmentation network for fast video object segmentation. IEEE Transactions On Circuits and Systems for Video Technology, 31(4), 1607-1617.
Journal: IEEE Transactions on Circuits and Systems for Video Technology 
Abstract: Semi-supervised video object segmentation is a task of propagating instance masks given in the first frame to the entire video. It is a challenging task since it usually suffers from heavy occlusions, large deformation, and large variations of objects. To alleviate these problems, many existing works apply time-consuming techniques such as fine-tuning, post-processing, or extracting optical flow, which makes them intractable for online segmentation. In our work, we focus on online semi-supervised video object segmentation. We propose a GCSeg (Guided Co-Segmentation) Network which is mainly composed of a Reference Module and a Co-segmentation Module, to simultaneously incorporate the short-term, middle-term, and long-term temporal inter-frame relationships. Moreover, we propose an Adaptive Search Strategy to reduce the risk of propagating inaccurate segmentation results in subsequent frames. Our GCSeg network achieves state-of-the-art performance on online semi-supervised video object segmentation on Davis 2016 and Davis 2017 datasets.
ISSN: 1558-2205
DOI: 10.1109/TCSVT.2020.3010293
Rights: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at:
Fulltext Permission: open
Fulltext Availability: With Fulltext
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