2020
DOI: 10.1109/access.2020.3024149
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An Effective Adversarial Attack on Person Re-Identification in Video Surveillance via Dispersion Reduction

Abstract: Person re-identification across a network of cameras, with disjoint views, has been studied extensively due to its importance in wide-area video surveillance. This is a challenging task due to several reasons including changes in illumination and target appearance, and variations in camera viewpoint and camera intrinsic parameters. The approaches developed to re-identify a person across different camera views need to address these challenges. More recently, neural network-based methods have been proposed to so… Show more

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Cited by 9 publications
(3 citation statements)
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“…But attackers can still observe the output through any input. Several attempts have been made on attacking Re-ID systems via black-box methods [24,30]. Although existing works demonstrate the feasibility of performing black-box attacks on classification and Re-ID vision systems, the research on person detection system has not yet been sufficiently investigated.…”
Section: Literature Reviewmentioning
confidence: 99%
“…But attackers can still observe the output through any input. Several attempts have been made on attacking Re-ID systems via black-box methods [24,30]. Although existing works demonstrate the feasibility of performing black-box attacks on classification and Re-ID vision systems, the research on person detection system has not yet been sufficiently investigated.…”
Section: Literature Reviewmentioning
confidence: 99%
“…However, the adversarial noise reduction mechanism has lower detection accuracy than others and has a problem of decrease in classifcation accuracy because the image flter can destroy the original object's characteristics. Zheng et al [18] also proposed an adversarial attack block mechanism that neutralizes adversarial noise with input image modifcation. Yuan et al used a randomized transform function for adversarial noise neutralization.…”
Section: Existing Work Adversarial Attack Block Mechanisms Can Be Cla...mentioning
confidence: 99%
“…Wang et al [20] proposed a learningto-misrank formulation to perturb the ranking of the system output, which drops one of the best ReID performances from 91.8% to 1.4% after being attacked. Zheng et al [21] extended the use of Dispersion Reduction (DR) to person ReID, and effectively attacked three different ReID networks using four different datasets. AEs from the ground truth and classify them into a new category.…”
Section: Adversarial Attacks In Person Reidmentioning
confidence: 99%