InfraQR: Edge-Placed QR-Inspired Structured Patch Attacks on Infrared Vision-Language Models
Infrared vision-language models are increasingly used for perception under low-light and adverse visual conditions, yet their robustness to localized structured perturbations remains underexplored. Existing infrared adversarial studies mainly focus on object detectors, leaving the security of infrared vision-language models less systematically examined. We present InfraQR, a QR-inspired structured patch attack for infrared vision-language models. Unlike localized attacks that attach perturbations to the target object, InfraQR places a compact structured patch along image boundaries and optimizes learnable grid cells through surrogate CLIP-style encoders. The resulting patch has a near-bin...
| Authors | Xin Li, Jiaju Han, Ma Yaqi et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 July 2026 |
| Last updated at source | 8 July 2026 |
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