捉迷藏：水印如何影响人脸识别？
Hide and Seek: How Does Watermarking Impact Face Recognition?
AI总结：
本文研究了数字水印对人脸识别模型有效性的影响，提出集生成、水印与识别的综合流水线，发现水印虽能实现稳健图像归属，但会导致识别准确率轻微下降，揭示了二者间的权衡。
摘要：
生成模型的最新进展彻底改变了高度逼真图像（包括人脸图像）的合成。这一技术发展无疑为人脸识别提供了帮助，例如通过训练数据增强来提高识别准确性和保护数据隐私。然而，它也带来了关于计算机生成图像的负责任使用和正确归属的新挑战。我们研究了数字水印（一种将所有权签名嵌入图像的技术）对人脸识别模型有效性的影响。我们提出了一种综合流水线，集成了人脸图像生成、水印嵌入和人脸识别，以系统地检验这一问题。所提出的水印方案基于编码器-解码器架构，能够成功地在真实和合成人脸图像中嵌入并恢复签名，同时保持其视觉保真度。通过大量实验，我们揭示，尽管水印能够实现稳健的图像归属，但它会导致人脸识别准确率轻微下降，这在具有挑战性姿势和表情的人脸图像中尤为明显。此外，我们发现直接在水印图像上训练人脸识别模型只能有限地缓解这种性能下降。我们的发现强调了水印与人脸识别准确率之间复杂的权衡。这项工作是在人脸识别中负责任地使用生成模型的关键一步，并旨在引发关于水印在生物识别中更广泛影响的讨论。
英文摘要：
The recent progress in generative models has revolutionized the synthesis of highly realistic images, including face images. This technological development has undoubtedly helped face recognition, such as training data augmentation for higher recognition accuracy and data privacy. However, it has also introduced novel challenges concerning the responsible use and proper attribution of computer generated images. We investigate the impact of digital watermarking, a technique for embedding ownership signatures into images, on the effectiveness of face recognition models. We propose a comprehensive pipeline that integrates face image generation, watermarking, and face recognition to systematically examine this question. The proposed watermarking scheme, based on an encoder-decoder architecture, successfully embeds and recovers signatures from both real and synthetic face images while preserving their visual fidelity. Through extensive experiments, we unveil that while watermarking enables robust image attribution, it results in a slight decline in face recognition accuracy, particularly evident for face images with challenging poses and expressions. Additionally, we find that directly training face recognition models on watermarked images offers only a limited alleviation of this performance decline. Our findings underscore the intricate trade off between watermarking and face recognition accuracy. This work represents a pivotal step towards the responsible utilization of generative models in face recognition and serves to initiate discussions regarding the broader implications of watermarking in biometrics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
