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In this paper, we propose Adversarial Semantic Contour (ASC), an MAP estimate of a Bayesian formulation of sparse attack with a deceived prior of object contour. The object contour prior effectively reduces the search space of pixel selection and improves the attack by introducing more semantic bias.
Mar 1, 2023
Sep 30, 2021 · We propose a novel method of Adversarial Semantic Contour (ASC) guided by object contour as prior. With this prior, we reduce the searching space.
A novel method of Adversarial Semantic Contour guided by object contour as prior is proposed, which outperforms the most commonly manually designed patterns ...
In this paper, we propose Adversarial Semantic Contour (ASC), an MAP estimate of a Bayesian formulation of sparse attack with a deceived prior of object ...
Abstract. Modern object detectors are vulnerable to adver- sarial examples, which brings potential risks to nu- merous applications, e.g., self-driving car.
Sep 29, 2021 · It can distinguish adversarial patches from original images. This detector can work with the types of objects in the image, for example, ...
Modern object detectors are vulnerable to adversarial examples, which brings potential risks to numerous applications, e.g., self-driving car.
Apr 1, 2023 · Modern object detectors are vulnerable to adversarial examples, which may bring risks to real-world applications.
In this paper, we extend adversarial examples to semantic segmentation and object detection which are much more difficult. Our observation is that both ...
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In this paper, we propose Adversarial Semantic Contour (ASC), an MAP estimate of a Bayesian formulation of sparse attack with a deceived prior of object contour ...