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Local Area Transform for Cross-Modality Correspondence Matching and Deep Scene Recognition
Furthermore, the reformulation of descriptors with LAT shows superiority to conventional methods, which is a promising result for the tasks of cross-spectral and modality correspondence matching.
DASC: Dense Adaptive Self-Correlation Descriptor for Multi-Modal and Multi-Spectral Correspondence
To further improve the matching quality and runtime efficiency, we propose a patch-wise receptive field pooling, in which a sampling pattern is optimized with a discriminative learning.
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