New DPC-VQA framework uses MLLMs for efficient video quality assessment

Researchers have developed DPC-VQA, a new framework for video quality assessment that leverages multimodal large language models (MLLMs). This approach decouples the perceptual capabilities of a frozen MLLM from a lightweight calibration branch, allowing for efficient adaptation to new scenarios without extensive retraining. DPC-VQA demonstrates competitive performance on both user-generated and AI-generated content benchmarks while significantly reducing trainable parameters and the need for MOS labels. AI

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

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• AI-generated content
• arXiv
• DPC-VQA
• multimodal large language model
• user-generated content
• Xinyue Li

• paper
• model release

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