Distracting Downpour: Adversarial Weather Attacks for Motion Estimation. (arXiv:2305.06716v1 [cs.CV])

Current adversarial attacks on motion estimation, or optical flow, optimize
small per-pixel perturbations, which are unlikely to appear in the real world.
In contrast, adverse weather conditions constitute a much more realistic threat
scenario. Hence, in this work, we present a novel attack on motion estimation
that exploits adversarially optimized particles to mimic weather effects like
snowflakes, rain streaks or fog clouds. At the core of our attack framework is
a differentiable particle rendering system that integrates particles (i)
consistently …

adversarial attacks arxiv attacks exploits flow novel optical flow per pixel small weather work world