外观
论文arXiv 2610.1426919 天前
RoboFake：深度伪造检测器准备好应对仿人面部机器人了吗？
原文链接：RoboFake: Are Deepfake Detectors Ready for Humanoid Face Robots?（arXiv 2610.14269 · 发布日期：2026-10-09）
RoboFake: Are Deepfake Detectors Ready for Humanoid Face Robots?
提出RoboFake问题，测试六个FaceForensics++检测器在实体、合成与渲染机器人脸视频上的表现。
核心要点
- 仿人面部机器人可形成镜头前真实物体的脸部伪造，像素未经编辑。
- 评测六个基于FaceForensics++训练的公开检测器，阈值固定并设人脸对照。
- 结果显示检测器反应来自脸部但不跟踪合成，部分实体机器人分数高于合成视频。
- 轻度JPEG压缩会使多数机器人帧低于部分检测器阈值；发布协议和代码。
验证范围与局限：验证范围为一个实体唇同步面部机器人、同一机器人的合成视频及渲染机器人脸。
英文摘要 (Abstract)
Humanoid face robots can now move their lips in sync with speech and show detailed facial expressions. Give such a robot the face of a real person and drive it with generated speech, and you get a face forgery that happens in front of the camera: the camera records a real object, and no pixel is edited. We call this a RoboFake. In this paper we ask what current deepfake detectors do when they see a robot face. We test six public detectors trained on FaceForensics++ on video of a physical lip-syncing face robot, on a synthesized video of the same robot, and on rendered robot faces. All thresholds are fixed on FaceForensics++, and every result is compared with real human faces that went through the same processing as the robot videos. At a threshold that flags 5% of real faces, three detectors flag almost every physical robot frame, while two flag fewer than 7%. A matched human control and masking show that the response comes from the face, not from the processing or the background. However, it does not track synthesis: with only the face visible, three of the six detectors give the physical robot a higher fake score than its synthesized video. The response is also fragile, and light JPEG compression is enough to push most robot frames below the threshold for some detectors. Our results suggest that current detectors flag today's robots because their faces do not look human, not because they recognize a forgery. We release our evaluation protocol and code, and state three testable hypotheses about realistic, interactive RoboFakes.
作者：Hao Chen, Junnan Xu
来源
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