Regularizing Visual Semantic Embedding With Contrastive Learning for Image-Text Matching
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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… read more here.
Keywords: image text; semantic embedding; visual semantic; text pairs ... See more keywords