A diffusion-based input purification module with pixel, semantic, and structural losses restores most tracking performance lost to a white-box adversarial attack, tested on three trackers.
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Towards Effective and Efficient Adversarial Defense with Diffusion Models for Robust Visual Tracking
A diffusion-based input purification module with pixel, semantic, and structural losses restores most tracking performance lost to a white-box adversarial attack, tested on three trackers.