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Paper Abstract and Keywords
Presentation 2019-12-06 10:10
Adversarial Examples for Monocular Depth Estimation CNN
Koichiro Yamanaka, Ryutaroh Matsumoto, Keita Takahashi, Toshiaki Fujii (Nagoya Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Adversarial examples for classification and object recognition problems using convolutional neural net- works (CNN) have attracted much attention in recent years. By adding perturbations to an input image of a CNN, adversarial attack is able to intentionally induce erroneous inferences. Adversarial attack is roughly classified into two types. The one is a method that slightly changes the pixel values of an entire input image, and the other is a method that overwrites a specific pattern (adversarial patch) on a local region of the input image. The latter method is called the adversarial patch attack, and recently real world attack was proposed by using this method. In other words, the classification CNN and the object recognition CNN could be deceived by taking a printed adversarial patch with a camera. However, adversarial attacks on regression problems have not been studied well. In this paper, we propose an adversarial attack method for regression problem, especially for monocular depth estimation CNN. We demonstrate that our method is capable of generating adversarial patches that can arbitrarily manipulate the output of the monocular depth estimation.
Keyword (in Japanese) (See Japanese page) 
(in English) Monocular Depth Estimation / CNN / Adversarial Examples / Adversarial Patch / / / /  
Reference Info. ITE Tech. Rep.
Paper #  
Date of Issue  
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
Committee IEICE-IE IEICE-CS IPSJ-AVM BCT  
Conference Date 2019-12-05 - 2019-12-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Aiina Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image coding, Communications and streaming technologies, etc. 
Paper Information
Registration To IEICE-CS 
Conference Code 2019-12-IE-CS-AVM-BCT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Adversarial Examples for Monocular Depth Estimation CNN 
Sub Title (in English)  
Keyword(1) Monocular Depth Estimation  
Keyword(2) CNN  
Keyword(3) Adversarial Examples  
Keyword(4) Adversarial Patch  
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1st Author's Name Koichiro Yamanaka  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Ryutaroh Matsumoto  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Keita Takahashi  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Toshiaki Fujii  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker
Date Time 2019-12-06 10:10:00 
Presentation Time 25 
Registration for IEICE-CS 
Paper #  
Volume (vol) 43 
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