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Visual descriptor learning seeks a projection to embed local descriptors (e.g., SIFT descriptors) into a new Euclidean space where pairs of matching descriptors (positive pairs) are better separated from pairs of non-matching descriptors (negative pairs). The original descriptors often confuse the positive pairs with the negative pairs, since local points labeled “non-matching” yield descriptors close...
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