Enhancing Tracking Robustness with Auxiliary Adversarial Defense Networks

arXiv:2402.17976v1 Announce Type: new
Abstract: Adversarial attacks in visual object tracking have significantly degraded the performance of advanced trackers by introducing imperceptible perturbations into images. These attack methods have garnered considerable attention from researchers in recent years. However, there is still a lack of research on designing adversarial defense methods specifically for visual object tracking. To address these issues, we propose an effective additional pre-processing network called DuaLossDef that eliminates adversarial perturbations during the tracking process. DuaLossDef is deployed ahead …

abstract advanced adversarial adversarial attacks arxiv attack methods attacks attention cs.cv defense designing images networks performance research researchers robustness tracking type visual