Dec 12, 2023 · As a new global similarity metric, central similarity can improve the efficiency and retrieval accuracy of hash learning. By introducing a new ...
Pairwise and triplet learnings only consider a pair/triplet of data at once, while our central similarity encourages all similar data points to collapse to the ...
Aug 1, 2019 · We propose a new \emph{global} similarity metric, termed as \emph{central similarity}, with which the hash codes of similar data pairs are encouraged to ...
Dec 3, 2024 · The proposed CSQ and CSQLC are generic and applicable to image and video hashing scenarios. We conduct extensive experiments on large-scale ...
As a new global similarity metric, central similarity can improve the efficiency and retrieval accuracy of hash learning. By introducing a new concept, hash ...
The Central Similarity Quantization (CSQ) is proposed, a new similarity metric with which the hash codes of similar data pairs are encouraged to approach a ...
Codes for paper: Central Similarity Quantization for Efficient Image and Video Retrieval, arxiv. We release all codes and configurations for image hashing.
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Dec 1, 2024 · Learnable Central Similarity Quantization for Efficient Image and Video Retrieval ; Graph Convolutional Network Discrete Hashing for Cross-Modal ...
CSQ takes as input similar and dissimilar pairs (images or videos). For image or video data, we use different types of CNNs for feature learning. After ...
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Learning to hash is an effective approach for constructing large-scale image retrieval systems [51]. Previous methods primarily use pointwise learning ...