通过重建高光谱图像，放大伪造痕迹，提升深度伪造检测效果。
Exposing DeepFakes via Hyperspectral Domain Mapping
- 从RGB图像重建31通道高光谱图，扩展分析维度。
- 在FaceForensics++数据集上显著优于仅用RGB的检测方法。
- 适合关注高维特征挖掘与伪造检测的科研人员。
当前生成与扩散模型产生的图像高度逼真，可欺骗人类感知及复杂自动化检测系统。现有检测方法多基于RGB空间，仅分析三个光谱通道。本文提出HSI-Detect，一种两阶段流程：将标准RGB输入重建为31通道高光谱图像，并在高光谱域进行检测。将输入表示扩展至更密集的光谱波段，能够增强在RGB域中微弱或不可见的篡改痕迹，尤其在特定频率波段表现明显。我们在FaceForensics++数据集上评估HSI-Detect，结果表明其持续优于仅依赖RGB的基线方法，展示了光谱域映射在深度伪造检测中的潜力。
原文摘要 · Abstract (English)
Modern generative and diffusion models produce highly realistic images that can mislead human perception and even sophisticated automated detection systems. Most detection methods operate in RGB space and thus analyze only three spectral channels. We propose HSI-Detect, a two-stage pipeline that reconstructs a 31-channel hyperspectral image from a standard RGB input and performs detection in the hyperspectral domain. Expanding the input representation into denser spectral bands amplifies manipulation artifacts that are often weak or invisible in the RGB domain, particularly in specific frequency bands. We evaluate HSI-Detect across FaceForensics++ dataset and show the consistent improvements over RGB-only baselines, illustrating the promise of spectral-domain mapping for Deepfake detection.
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