Privacy-Preserving Object Detection for Vision Transformer-Based Models

2026-08-20

AI Summary

本文提出了一种基于感知加密的隐私保护方法，用于视觉变换器模型的对象检测任务，同时保持高精度。

Abstract

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.

Problem

• Privacy-Preserving
• Object Detection
• Vision Transformer
• Sensitive Visual Information

Innovation

• Privacy-Preserving
• Object Detection
• Vision Transformer
• Perceptual Encryption
• Domain Adaptation