AI假视频检测在真实危机场景全面失灵
现在的AI视频生成器能伪造战争、灾难等真实危机事件，而最新的系统评测显示：现有检测器在真实场景下几乎全部失效，而且越接近真实、越被社交传播，检测越难。研究者构建了包含17,886个视频的基准，覆盖10类社会风险场景，测试了7种传统检测器、10种零样本多模态模型和2种专门微调的模型，结果没有任何一类能稳定泛化。更关键的是，那些能骗过人类的视频，同样也能骗过检测器——这意味着在真实危机中，AI伪造视频的威胁比我们以为的更严重。
📄 原文摘要(英文)
Recent video generators can fabricate realistic depictions of wars, disasters, public emergencies, and other real-world crises, creating substantial risks of misinformation. Existing benchmarks, however, provide limited evidence on detector and generator behavior in such settings, including how detectability varies with generation conditions, how people perceive generated videos, and whether detectors remain reliable during social dissemination. To address this gap, we introduce RA-Bench, a benchmark for AI-generated video detection that uses Real videos as Anchors. RA-Bench contains 17,886 videos, comprising 1,830 real-video anchors across 10 social-risk categories and 16,056 generated clips from four open-source and five closed-source generators. Based on RA-Bench, we organize our evaluation along three dimensions. We first assess detector generalization across seven traditional detectors, ten zero-shot multimodal models under three review settings, and two MLLMs specifically fine-tuned on AI-generated video detection. Across these methods, none of the three detector families generalizes consistently across RA-Bench instances. We then examine how detectability varies with generation quality, conditioning information, and sampling seeds. These analyses show that generation properties affect detector families differently, while source-level detection patterns remain stable across seeds. Finally, we study human authenticity judgments and detector reliability during social dissemination. We find that videos that mislead people are also difficult for current detectors, and that social dissemination makes detection harder. Together, these findings show that current methods struggle to detect realistic AI-generated videos, highlighting the need for detectors robust to evolving video generators.