LGCNet: Feature Enhancement and Consistency Learning Based on Local and Global Coherence Network for Correspondence Selection
Tzu-Han Wu,Kuan-Wen Chen,Tzu-Han Wu,Kuan-Wen Chen
Correspondence selection, a crucial step in many computer vision tasks, aims to distinguish between inliers and outliers from putative correspondences. The coherence of correspondences is often used for predicting inlier probability, but it is difficult for neural networks to extract coherence contexts based only on quadruple coordinates. To overcome this difficulty, we propose enhancing the preli...
