SOURCE-LINKED INTELLIGENCE
IMFD: End-to-end Multi-Face Forgery Detection through Instruction-based Large Vision-Language Models
The rapid increase of deepfakes has raised significant concerns due to their spread on social media. Traditional multi-face forgery detectors crop and verify each face independently, ignoring background context and inter-face relationships, which often yields suboptimal performance. To overcome these limitations, we leverage instruction-based Large Vision-Language Models (LVLMs), which can interpret entire images and follow complex textual instructions. We propose a simple yet effective single-stage multi-face forgery detector, called IMFD (Instruction-based Multi-face Forgery Detector), which
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T04:40:20.000Z
First collected: 2026-09-19T20:28:21.856Z. This is not the publication date.