通过高光谱域映射揭露深度伪造（DeepFakes）
Exposing DeepFakes via Hyperspectral Domain Mapping
AI总结：
针对现有RGB域深度伪造检测方法易遗漏微弱篡改伪影的问题，本文提出两阶段HSI-Detect框架，将RGB输入重建为31通道高光谱图像后开展检测，在FaceForensics++上性能优于RGB基线，验证了光谱域映射的检测价值。
摘要：
现代生成模型与扩散模型可生成极具真实感的图像，这类图像不仅能误导人类感知，甚至可骗过精密的自动检测系统。现有大多数检测方法在RGB空间运行，仅能分析3个光谱通道。本文提出HSI-Detect，这是一种两阶段流水线，可从标准RGB输入重建出31通道的高光谱图像，并在高光谱域执行检测。将输入表征扩展至更密集的光谱带，能够放大在RGB域通常较微弱甚至不可见的篡改伪影，特定频率带的伪影放大效果尤为明显。本文在FaceForensics++数据集上对HSI-Detect开展评估，结果显示其性能相较仅使用RGB的基线模型实现稳定提升，证明了光谱域映射在深度伪造检测任务中的应用潜力。
英文摘要：
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.
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。
