5 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 1 cited
Adversarial Catoptric Light: An Effective, Stealthy and Robust Physical-World Attack to DNNs
Chengyin Hu, Weiwen Shi
Deep neural networks (DNNs) have demonstrated exceptional success across various tasks, underscoring the need to evaluate the robustness of advanced DNNs. However, traditional meth…
cs.CV2022★ 5 cited
Adversarial Laser Spot: Robust and Covert Physical-World Attack to DNNs
Chengyin Hu, Yilong Wang, Kalibinuer Tiliwalidi +1
Most existing deep neural networks (DNNs) are easily disturbed by slight noise. However, there are few researches on physical attacks by deploying lighting equipment. The light-bas…
cs.CV2022★ 2 cited
Adversarial Neon Beam: A Light-based Physical Attack to DNNs
Chengyin Hu, Weiwen Shi, Wen Li
In the physical world, deep neural networks (DNNs) are impacted by light and shadow, which can have a significant effect on their performance. While stickers have traditionally bee…