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Losing the name before the box: measuring and repairing what narrow fine-tuning costs a detector outside its deployment vocabulary

Bui, Trung Minh et al.
arXiv (All) · Papers
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computer-vision-and-pattern-recognitionmachine-learningrobotics
A detector pretrained on a broad corpus is fine-tuned on a narrow domain, its in-domain accuracy improves, and it ships. We ask what happens meanwhile to its coverage of objects the vocabulary never names, which in obstacle detection and inspection carry the risk. No in-domain test set holds an exam
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