ASL-PAR creates universal adversarial noise using label and semantic perturbation, dropping PromptPAR's mean accuracy by up to 40 points on standard PAR benchmarks, while a filter-and-prompt defense restores most of the drop.
Pedestrian attribute recognition via clip based prompt vision-language fusion,
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Adversarial Semantic and Label Perturbation Attack for Pedestrian Attribute Recognition
ASL-PAR creates universal adversarial noise using label and semantic perturbation, dropping PromptPAR's mean accuracy by up to 40 points on standard PAR benchmarks, while a filter-and-prompt defense restores most of the drop.