Privacy-Preserving Object Detection for Vision Transformer-Based Models
We propose a novel object detection method that enables us to protect sensitive visual information of test images. Previous studies considering visual information protection focus on image classification tasks. This paper proposes an object detection method using perceptual encryption for the first time. The proposed method can achieve almost the same accuracy as that of models without any protection by utilizing the embedding structure of the Vision Transformer (ViT) and a domain adaptation technique with keys. In experiments, the effectiveness of the proposed method is verified in terms of accuracy and visual protection under the use of ViTdet, which is a ViT-based object detection model.
| Authors | Homare Sueyoshi, Kiyoshi Nishikawa, Hitoshi Kiya |
|---|---|
| Primary category | cs.CR |
| Published | 21 August 2026 |
| Last updated at source | 21 August 2026 |
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