Multimodal fusion of MLLM-generated text embeddings and visual features improves retrieval for forensic tattoo and face matching tasks across images, descriptions, and sketches.
Approach for tattoo detection and identification based on yolov5 and similarity distance
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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.