International Journal of Computational Intelligence Systems

Volume 14, Issue 1, 2021, Pages 886 - 895

Few-Shot Image Segmentation Based on Dual Comparison Module and Sequential k-Shot Integration

Authors
Chencong Xing1, *, ORCID, Shujing Lyu2, ORCID, Yue Lu2, ORCID
1School of Computer Science and Technology, East China Normal University, Shanghai, 200241, China
2Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, 200241, China
*Corresponding author. Email: 51184506047@stu.ecnu.edu.cn
Corresponding Author
Chencong Xing
Received 12 January 2021, Accepted 3 February 2021, Available Online 1 March 2021.
DOI
10.2991/ijcis.d.210212.003How to use a DOI?
Keywords
Few-shot learning; Image segmentation; Dual comparison module; Convolutional-gated recurrent unit
Abstract

Few-shot image segmentation intends to segment query images (test images) given only a few support samples with annotations. However, previous works ignore the impact of the object scales, especially in the support images. Meanwhile, current models only work on images with the similar size of the object and rarely test on other domains. This paper proposes a new few-shot segmentation model named DCNet, which fully exploits the support set images and their annotations and is able to generalize to the test images with unseen objects of various scales. The idea is to gradually compare the features from the query and the support image, and refine the features for the query. Furthermore, a sequential k-shot comparison method is proposed based on the ConvGRU to integrate features from multiple annotated support images. Experiments on Pascal VOC dataset and X-ray Security Images demonstrate the excellent generalization performance of our model.

Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
14 - 1
Pages
886 - 895
Publication Date
2021/03/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.210212.003How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Chencong Xing
AU  - Shujing Lyu
AU  - Yue Lu
PY  - 2021
DA  - 2021/03/01
TI  - Few-Shot Image Segmentation Based on Dual Comparison Module and Sequential k-Shot Integration
JO  - International Journal of Computational Intelligence Systems
SP  - 886
EP  - 895
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.210212.003
DO  - 10.2991/ijcis.d.210212.003
ID  - Xing2021
ER  -