UniShield introduces a knowledge-graph-informed multimodal framework that improves unified detection of physical and digital face attacks through instruction tuning and consistency-optimized reasoning.
Vlforgery face triad: Detection, localization and attribution via multimodal large language models
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Multimodal fusion of MLLM-generated text embeddings and visual features improves retrieval for forensic tattoo and face matching tasks across images, descriptions, and sketches.
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UniShield: Unified Face Attack Detection via KG-Informed Multimodal Reasoning
UniShield introduces a knowledge-graph-informed multimodal framework that improves unified detection of physical and digital face attacks through instruction tuning and consistency-optimized reasoning.
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Bridging the Modality Gap in Forensic Image Retrieval
Multimodal fusion of MLLM-generated text embeddings and visual features improves retrieval for forensic tattoo and face matching tasks across images, descriptions, and sketches.