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MCNet: Multiscale Clustering Network for Two-View Geometry Learning and Feature Matching

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摘要 Dear Editor, The main components of multi-view geometry and computer vision are robust pose estimation and feature matching. This letter discusses how to recover two-view geometry and match features between a pair of images, and presents MCNet(a multiscale clustering network) as an algorithm for extracting multiscale features. It can identify the true inliers from the established putative correspondences, where outliers may degenerate the geometry estimation. In particular, the proposed MCNet is based on graph clustering.
出处 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2023年第6期1507-1509,共3页 自动化学报(英文版)
基金 supported by the National Natural Science Foundation of China(61703260,62173252)。
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