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Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3178899
Abstract: Learning visual semantic embedding for image-text matching has achieved high success by using triplet loss to pull positive image-text pairs which share similar semantic meaning and to push negative image-text pairs which share different semantic…
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Keywords:
image text;
semantic embedding;
visual semantic;
text pairs ... See more keywords