Papers by Giacomo Nebbia

1 papers
Synonym relations affect object detection learned on vision-language data (2024.findings-naacl)

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Challenge: a recent study shows that vision-language models that accept textual input are not robust to variations in how input is provided.
Approach: They propose two approaches to improve vision-language object detectors' performance . they use back-translation and class embedding enrichment to improve their models .
Outcome: The proposed approaches improve performance on synonyms from mAP@0.3=33.87% to 37.93%.

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