ForensicZoom: Adaptive Visual Inspection with Multimodal LLMs for Industrial-Grade Face Forgery Detection
Leveraging Multimodal LLMs to enhance precision and adaptability in industrial-grade deepfake detection.
Reliable face forgery detection is critical to the security of online identity verification systems, where missed attacks compromise security and excessive false positives disrupt legitimate users. Specialized forensic detectors achieve strong detection performance but provide li...
ArXiv CS.CV
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ForensicZoom represents a significant shift by integrating multimodal LLMs into industrial forgery detection, allowing for more nuanced, adaptive inspection of complex deepfake threats. This approach bridges the gap between rigid forensic tools and the contextual reasoning capabilities required to reduce false positives in high-stakes identity verification.
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