MaSC is a masked similarity metric that decomposes concept-driven image generation evaluation into subject-specific preservation and background-based prompt following using SigLIP2 embeddings, outperforming global baselines on human correlation and identity benchmarks.
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MaSC: A Masked Similarity Metric for Evaluating Concept-Driven Generation
MaSC is a masked similarity metric that decomposes concept-driven image generation evaluation into subject-specific preservation and background-based prompt following using SigLIP2 embeddings, outperforming global baselines on human correlation and identity benchmarks.