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Published in 2023 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2021.3139210
Abstract: For visual-semantic embedding, the existing methods normally treat the relevance between queries and candidates in a bipolar way – relevant or irrelevant, and all “irrelevant” candidates are uniformly pushed away from the query by an…
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Keywords:
relevance;
semantic embedding;
visual semantic;
ladder loss ... See more keywords