Multimodal Large Language Model for HDR & SDR Video Quality Measurement

This paper presents our solutions for NR track in ICME2025 Generalizable HDR & SDR Video Quality Measurement Grand Challenge, where we achieved 0.945 SROCC score in the test set. In our approach, we propose Spatial Window Sampling to learn fine-grained features for robust video quality measurement. Finally, we further enhance the performance of video quality measurement by employing an average fusion strategy.

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Published
2025-06-30
DOI
https://doi.org/10.1109/icmew68306.2025.11152187
Primary Topic
Image Enhancement Techniques
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article
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article

Multimodal Large Language Model for HDR & SDR Video Quality Measurement

Baojun Li
Image Enhancement Techniques
article

Multimodal Large Language Model for HDR & SDR Video Quality Measurement

Baojun Li
article en

Abstract

This paper presents our solutions for NR track in ICME2025 Generalizable HDR & SDR Video Quality Measurement Grand Challenge, where we achieved 0.945 SROCC score in the test set. In our approach, we propose Spatial Window Sampling to learn fine-grained features for robust video quality measurement. Finally, we further enhance the performance of video quality measurement by employing an average fusion strategy.

Guangzhou Mechanical Engineering Research Institute (China) (CN)
Openalex Percentile: Top 76%
Image Enhancement Techniques
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Multimodal Large Language Model for HDR & SDR Video Quality Measurement — Baojun Li · (2025) | TGRS Research Map | TGRS