AI RESEARCH
Learning to Look before Learning to Like: Incorporating Human Visual Cognition into Aesthetic Quality Assessment
arXiv CS.CV
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ArXi:2604.15853v1 Announce Type: new Automated Aesthetic Quality Assessment (AQA) treats images primarily as static pixel vectors, aligning predictions with human-rating scores largely through semantic perception. However, this paradigm diverges from human aesthetic cognition, which arises from dynamic visual exploration shaped by scanning paths, processing fluency, and the interplay between bottom-up salience and top-down intention. We