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Subjective And Objective Quality Assessment Of Mobile Gaming Video

Shaoguo Wen
  • Function : Author
Junle Wang
  • Function : Author
Ximing Chen
  • Function : Author
Yanqing Jing
  • Function : Author
Patrick Patrick Le Callet


Nowadays, with the vigorous expansion and development of gaming video streaming techniques and services, the expectation of users, especially the mobile phone users, for higher quality of experience is also growing swiftly. As most of the existing research focuses on traditional video streaming, there is a clear lack of both subjective study and objective quality models that are tailored for quality assessment of mobile gaming content. To this end, in this study, we first present a brand new Tencent Gaming Video dataset containing 1293 mobile gaming sequences encoded with three different codecs. Second, we propose an objective quality framework, namely Efficient hard-RAnk Quality Estimator (ERAQUE), that is equipped with (1) a novel hard pairwise ranking loss, which forces the model to put more emphasis on differentiating similar pairs; (2) an adapted model distillation strategy, which could be utilized to compress the proposed model efficiently without causing significant performance drop. Extensive experiments demonstrate the efficiency and robustness of our model.
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Dates and versions

hal-04043195 , version 1 (23-03-2023)



Shaoguo Wen, Suiyi Ling, Junle Wang, Ximing Chen, Yanqing Jing, et al.. Subjective And Objective Quality Assessment Of Mobile Gaming Video. 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022), May 2022, Singapour, Singapore. pp.1810-1814, ⟨10.1109/ICASSP43922.2022.9746547⟩. ⟨hal-04043195⟩
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