New framework uses text and images to assess image complexity

Researchers have developed a new framework called Describe-to-Score (D2S) that integrates textual semantics with visual features to assess image complexity. This multimodal approach aims to capture high-level semantic cues that traditional visual-only methods miss. D2S uses caption-derived semantics during training to regularize visual complexity modeling, allowing for vision-only inference without additional overhead. The framework has demonstrated state-of-the-art performance on the IC9600 benchmark and shows competitiveness in no-reference image quality assessment tasks. AI

IMPACT This framework could improve image analysis tasks by incorporating semantic understanding into complexity assessment.

RANK_REASON The cluster contains an academic paper detailing a new framework for image complexity assessment. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

• Describe-to-Score
• IC9600
• Shipeng Liu

• paper
• other

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