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arXiv Computer Vision By Homare Sueyoshi, Kiyoshi Nishikawa, Hitoshi Kiya

Privacy-Preserving Object Detection for Vision Transformer-Based Models

Read the original on arXiv Computer Vision →

The paper introduces a new object detection approach that protects sensitive visual data in test images. It is the first to apply perceptual encryption to object detection, leveraging the embedding structure of Vision Transformers and a key-based domain adaptation to maintain accuracy comparable to unprotected models. Experiments on ViTdet confirm the method’s effectiveness in both accuracy and visual protection.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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