MICo-150K is a new 150K-image dataset with 7 tasks, a De&Re real-image subset, MICo-Bench, and Weighted-Ref-VIEScore metric that improves AI models for generating consistent composites from arbitrary numbers of reference images.
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Adapting DINOv3 via SimMIM and composite metric learning on U.S. IDs yields 99.83% Canadian layout accuracy and surfaces 276 fraud cases (222 missed by prior detectors) in 20k Canadian IDs via embedding analysis.
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MICo-150K: A Comprehensive Dataset Advancing Multi-Image Composition
MICo-150K is a new 150K-image dataset with 7 tasks, a De&Re real-image subset, MICo-Bench, and Weighted-Ref-VIEScore metric that improves AI models for generating consistent composites from arbitrary numbers of reference images.
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Layout-Aware Representation Learning for Open-Set ID Fraud Discovery
Adapting DINOv3 via SimMIM and composite metric learning on U.S. IDs yields 99.83% Canadian layout accuracy and surfaces 276 fraud cases (222 missed by prior detectors) in 20k Canadian IDs via embedding analysis.