AestheticNet improves aesthetic quality assessment by fusing a gaze-aligned visual encoder pre-trained on eye-tracking data with semantic encoders via cross-attention, yielding consistent gains over semantic-only baselines.
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A literature survey that categorizes high-level abstract concept image classification tasks in CV into semantic clusters and identifies persistent challenges and opportunities for hybrid AI approaches.
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Learning to Look before Learning to Like: Incorporating Human Visual Cognition into Aesthetic Quality Assessment
AestheticNet improves aesthetic quality assessment by fusing a gaze-aligned visual encoder pre-trained on eye-tracking data with semantic encoders via cross-attention, yielding consistent gains over semantic-only baselines.
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Seeing the Intangible: Survey of Image Classification into High-Level and Abstract Categories
A literature survey that categorizes high-level abstract concept image classification tasks in CV into semantic clusters and identifies persistent challenges and opportunities for hybrid AI approaches.