A Privacy-Preserving Semantic-Segmentation Method Using Domain-Adaptation Technique

• URL: http://arxiv.org/abs/2507.12730v1
• Date: Thu, 17 Jul 2025 02:14:50 GMT
• Title: A Privacy-Preserving Semantic-Segmentation Method Using Domain-Adaptation Technique
• Abstract summary: We propose a privacy-preserving semantic-segmentation method for applying perceptual encryption to images used for model training and test images.<n>This method also provides almost the same accuracy as models without any encryption.
• Score: 5.311735227179715
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose a privacy-preserving semantic-segmentation method for applying perceptual encryption to images used for model training in addition to test images. This method also provides almost the same accuracy as models without any encryption. The above performance is achieved using a domain-adaptation technique on the embedding structure of the Vision Transformer (ViT). The effectiveness of the proposed method was experimentally confirmed in terms of the accuracy of semantic segmentation when using a powerful semantic-segmentation model with ViT called Segmentation Transformer.

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