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Progressive Correspondence Pruning by Consensus Learning

Progressive Correspondence Pruning by Consensus Learning

Correspondence pruning aims to correctly remove false matches (outliers) from an initial set of putative correspondences. The pruning process is challenging since putative matches are typically extremely unbalanced, largely dominated by outliers, and the random distribution of such outliers further complicates the learning process for learning-based methods. To address this …