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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance

February 1, 2023

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Authors

Vignesh Srinivasan

Fraunhofer HHI


Klaus-Robert Müller

TU Berlin


Wojciech Samek

Fraunhofer HHI


Shinichi Nakajima

TU Berlin


DOI:

10.1609/aaai.v34i04.6042


Abstract:

Unpaired image-to-image domain translation involves the task of transferring an image in one domain to another domain without having pairs of data for supervision. Several methods have been proposed to address this task using Generative Adversarial Networks (GANs) and cycle consistency constraint enforcing the translated image to be mapped back to the original domain. This way, a Deep Neural Network (DNN) learns mapping such that the input training distribution transferred to the target domain matches the target training distribution. However, not all test images are expected to fall inside the data manifold in the input space where the DNN has learned to perform the mapping very well. Such images can have a poor mapping to the target domain. In this paper, we propose to perform Langevin dynamics, which makes a subtle change in the input space bringing them close to the data manifold, producing benign examples. The effect is significant improvement of the mapped image on the target domain. We also show that the score function estimation by denoising autoencoder (DAE), can practically be replaced with any autoencoding structure, which most image-to-image translation methods contain intrinsically due to the cycle consistency constraint. Thus, no additional training is required. We show advantages of our approach for several state-of-the-art image-to-image domain translation models. Quantitative evaluation shows that our proposed method leads to a substantial increase in the accuracy to the target label on multiple state-of-the-art image classifiers, while qualitative user study proves that our method better represents the target domain, achieving better human preference scores.

Topics: AAAI

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HOW TO CITE:

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance Proceedings of the AAAI Conference on Artificial Intelligence (2020) 5842-5850.

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance AAAI 2020, 5842-5850.

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima (2020). Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. Proceedings of the AAAI Conference on Artificial Intelligence, 5842-5850.

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima. Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.5842-5850.

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima. 2020. Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. "Proceedings of the AAAI Conference on Artificial Intelligence". 5842-5850.

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima. (2020) "Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance", Proceedings of the AAAI Conference on Artificial Intelligence, p.5842-5850

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima, "Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance", AAAI, p.5842-5850, 2020.

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima. "Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.5842-5850.

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima. "Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 5842-5850.

Vignesh Srinivasan||Klaus-Robert Müller||Wojciech Samek||Shinichi Nakajima. Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. AAAI[Internet]. 2020[cited 2023]; 5842-5850.


ISSN: 2374-3468


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