FaceTracer：揭示换脸图像和视频中的源身份以预防欺诈
FaceTracer: Unveiling Source Identities from Swapped Face Images and Videos for Fraud Prevention
AI总结：
FaceTracer是首个非侵入式框架，通过解耦模块抑制目标身份并提取源身份特征，从换脸图像或视频中追踪源人物，有效预防欺诈，且对未知换脸方法具有强迁移性和鲁棒性。
摘要：
随着深度学习的发展，换脸技术迅速进步，导致其广泛使用，并引发了对潜在滥用的日益担忧，尤其是在欺诈案件中。尽管许多工作集中于检测换脸图像或视频，但这些方法不足以追踪欺诈活动背后的恶意用户。侵入式水印方法也无法追踪未标记的身份，限制了其实用性。为应对这些挑战，我们引入了FaceTracer，这是第一个专门设计用于从换脸图像或视频中追踪源人物身份的非侵入式框架。具体而言，FaceTracer利用一个解耦模块，有效抑制与目标人物相关的身份信息，同时隔离源人物的身份特征。这使我们能够提取稳健的身份信息，直接将换脸内容与原始个体关联起来，有助于揭示欺诈活动背后的行为者。大量实验证明了FaceTracer在各种换脸技术上的有效性，成功识别换脸内容中的源人物，并能够追踪参与欺诈活动的恶意行为者。此外，FaceTracer对未见过的换脸方法（包括商业应用）表现出强大的迁移性，并对传输失真和自适应攻击具有鲁棒性。我们的代码可在https://github.com/zzy224/FaceTracer获取。
英文摘要：
Face-swapping techniques have advanced rapidly with the evolution of deep learning, leading to widespread use and growing concerns about potential misuse, especially in cases of fraud. While many efforts have focused on detecting swapped face images or videos, these methods are insufficient for tracing the malicious users behind fraudulent activities. Intrusive watermark-based approaches also fail to trace unmarked identities, limiting their practical utility. To address these challenges, we introduce FaceTracer, the first non-intrusive framework specifically designed to trace the identity of the source person from swapped face images or videos. Specifically, FaceTracer leverages a disentanglement module that effectively suppresses identity information related to the target person while isolating the identity features of the source person. This allows us to extract robust identity information that can directly link the swapped face back to the original individual, aiding in uncovering the actors behind fraudulent activities. Extensive experiments demonstrate FaceTracer's effectiveness across various face-swapping techniques, successfully identifying the source person in swapped content and enabling the tracing of malicious actors involved in fraudulent activities. Additionally, FaceTracer shows strong transferability to unseen face-swapping methods including commercial applications and robustness against transmission distortions and adaptive attacks.Our code is available at: https://github.com/zzy224/FaceTracer.
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。
