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Volume 11
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10.3390/app11104648
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Article

Semantic Matching Based on Semantic Segmentation and Neighborhood Consensus

by
Huaiyuan Xu
,
Xiaodong Chen
*,
Huaiyu Cai
,
Yi Wang
,
Haitao Liang
and
Haotian Li
Key Laboratory of Opto-Electronics Information Technology, Ministry of Education, School of Precision Instrument & Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2021, 11(10), 4648; https://doi.org/10.3390/app11104648
Submission received: 25 April 2021 / Revised: 15 May 2021 / Accepted: 17 May 2021 / Published: 19 May 2021
(This article belongs to the Topic Applied Computer Vision and Pattern Recognition)
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Abstract

Establishing dense correspondences across semantically similar images is a challenging task, due to the large intra-class variation caused by the unconstrained setting of images, which is prone to cause matching errors. To suppress potential matching ambiguity, NCNet explores the neighborhood consensus pattern in the 4D space of all possible correspondences, which is based on the assumption that the correspondence is continuous in space. We retain the neighborhood consensus constraint, while introducing semantic segmentation information into the features, which makes them more distinguishable and reduces matching ambiguity from a feature perspective. Specifically, we combine the semantic segmentation network to extract semantic features and the 4D convolution to explore 4D-space context consistency. Experiments demonstrate that our algorithm has good semantic matching performances and semantic segmentation information can improve semantic matching accuracy.
Keywords: semantic matching; semantic segmentation; spatial context consensus semantic matching; semantic segmentation; spatial context consensus

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MDPI and ACS Style

Xu, H.; Chen, X.; Cai, H.; Wang, Y.; Liang, H.; Li, H. Semantic Matching Based on Semantic Segmentation and Neighborhood Consensus. Appl. Sci. 2021, 11, 4648. https://doi.org/10.3390/app11104648

AMA Style

Xu H, Chen X, Cai H, Wang Y, Liang H, Li H. Semantic Matching Based on Semantic Segmentation and Neighborhood Consensus. Applied Sciences. 2021; 11(10):4648. https://doi.org/10.3390/app11104648

Chicago/Turabian Style

Xu, Huaiyuan, Xiaodong Chen, Huaiyu Cai, Yi Wang, Haitao Liang, and Haotian Li. 2021. "Semantic Matching Based on Semantic Segmentation and Neighborhood Consensus" Applied Sciences 11, no. 10: 4648. https://doi.org/10.3390/app11104648

APA Style

Xu, H., Chen, X., Cai, H., Wang, Y., Liang, H., & Li, H. (2021). Semantic Matching Based on Semantic Segmentation and Neighborhood Consensus. Applied Sciences, 11(10), 4648. https://doi.org/10.3390/app11104648

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