DPC-VQA decouples a frozen MLLM perceptual prior from a lightweight residual calibration branch to adapt video quality assessment to new scenarios with under 2% trainable parameters and 20% of typical MOS labels.
Bovik, and Zhengzhong Tu
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
rPPG-VQA filters in-the-wild videos using signal-level SNR consensus and scene-level MLLM interference detection, then applies two-stage adaptive sampling to produce unsupervised rPPG models with substantially higher benchmark accuracy.
Retraining VMAF on teleoperation-specific subjective ratings reduces RMSE from 10.36 to 8.83 and MAD from 8.71 to 6.38 compared to the standard model.
citing papers explorer
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DPC-VQA: Decoupling Quality Perception and Residual Calibration for Video Quality Assessment
DPC-VQA decouples a frozen MLLM perceptual prior from a lightweight residual calibration branch to adapt video quality assessment to new scenarios with under 2% trainable parameters and 20% of typical MOS labels.
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rPPG-VQA: A Video Quality Assessment Framework for Unsupervised rPPG Training
rPPG-VQA filters in-the-wild videos using signal-level SNR consensus and scene-level MLLM interference detection, then applies two-stage adaptive sampling to produce unsupervised rPPG models with substantially higher benchmark accuracy.
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Beyond VMAF: Towards Application-Specific Metrics for Teleoperation Video
Retraining VMAF on teleoperation-specific subjective ratings reduces RMSE from 10.36 to 8.83 and MAD from 8.71 to 6.38 compared to the standard model.