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• W2560741668 abstract "We propose a novel measure for template matching named Deformable Diversity Similarity - based on the diversity of feature matches between a target image window and the template. We rely on both local appearance and geometric information that jointly lead to a powerful approach for matching. Our key contribution is a similarity measure, that is robust to complex deformations, significant background clutter, and occlusions. Empirical evaluation on the most up-to-date benchmark shows that our method outperforms the current state-of-the-art in its detection accuracy while improving computational complexity." @default.
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• W2560741668 date "2017-07-01" @default.
• W2560741668 modified "2023-10-16" @default.
• W2560741668 title "Template Matching with Deformable Diversity Similarity" @default.
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• W2560741668 doi "https://doi.org/10.1109/cvpr.2017.144" @default.
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