2 papers
cs.CV2020
Black-box Adversarial Attacks on Monocular Depth Estimation Using Evolutionary Multi-objective Optimization
Renya Daimo, Satoshi Ono, Takahiro Suzuki
This paper proposes an adversarial attack method to deep neural networks (DNNs) for monocular depth estimation, i.e., estimating the depth from a single image. Single image depth e…
cs.CV2019
Adversarial Example Generation using Evolutionary Multi-objective Optimization
Takahiro Suzuki, Shingo Takeshita, Satoshi Ono
This paper proposes Evolutionary Multi-objective Optimization (EMO)-based Adversarial Example (AE) design method that performs under black-box setting. Previous gradient-based meth…