AUTHOR=Ke Junjie , Zhang Tianhao , Wang Yilin , Milanfar Peyman , Yang Feng TITLE=MRET: Multi-resolution transformer for video quality assessment JOURNAL=Frontiers in Signal Processing VOLUME=3 YEAR=2023 URL=https://www.frontiersin.org/journals/signal-processing/articles/10.3389/frsip.2023.1137006 DOI=10.3389/frsip.2023.1137006 ISSN=2673-8198 ABSTRACT=

No-reference video quality assessment (NR-VQA) for user generated content (UGC) is crucial for understanding and improving visual experience. Unlike video recognition tasks, VQA tasks are sensitive to changes in input resolution. Since large amounts of UGC videos nowadays are 720p or above, the fixed and relatively small input used in conventional NR-VQA methods results in missing high-frequency details for many videos. In this paper, we propose a novel Transformer-based NR-VQA framework that preserves the high-resolution quality information. With the multi-resolution input representation and a novel multi-resolution patch sampling mechanism, our method enables a comprehensive view of both the global video composition and local high-resolution details. The proposed approach can effectively aggregate quality information across different granularities in spatial and temporal dimensions, making the model robust to input resolution variations. Our method achieves state-of-the-art performance on large-scale UGC VQA datasets LSVQ and LSVQ-1080p, and on KoNViD-1k and LIVE-VQC without fine-tuning.