Journal article

Hierarchical Paired Channel Fusion Network for Street Scene Change Detection

Yinjie Lei, Duo Peng, Pingping Zhang, Qiuhong Ke, Haifeng Li

IEEE TRANSACTIONS ON IMAGE PROCESSING | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2021

Abstract

Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging task in the computer vision community. The intuitive way to solve the SSCD task is to fuse the extracted image feature pairs, and then directly measure the dissimilarity parts for producing a change map. Therefore, the key for the SSCD task is to design an effective feature fusion method that can improve the accuracy of the corresponding change maps. To this end, we present a novel Hierarchical Paired Channel Fusion Network (HPCFNet), which utilizes the adaptive fusion of paired feature channels. Specifically, the fe..

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Grants

Awarded by National Natural Science Foundation of China (NNSFC)


Awarded by Key Research and Development Program of Sichuan Province


Funding Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (NNSFC) under Grant 61403265, Grant 41571397, Grant 61725202, Grant 61751212, and Grant 61771088; and in part by the Key Research and Development Program of Sichuan Province under Grant 2019YFG0409.