2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDSMR-1.5
Paper Title VIDEO QUALITY ASSESSMENT OF USER GENERATED CONTENT: A BENCHMARK STUDY AND A NEW MODEL
Authors Zhengzhong Tu, Chia-Ju Chen, University of Texas at Austin, United States; Yilin Wang, Neil Birkbeck, Balu Adsumilli, Google Inc., United States; Alan Bovik, University of Texas at Austin, United States
SessionSMR-1: Image and Video Quality Assessment
LocationArea F
Session Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Poster
Topic Image and Video Sensing, Modeling, and Representation: Perception and quality models for images & video
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Recent years have witnessed an explosion of user-generated content (UGC) shared and streamed over the Internet. Accordingly, there is a great need for accurate video quality assessment (VQA) models for consumer or UGC videos to monitor, control, and optimize this vast content. Here we contribute to advancing the UGC-VQA problem by conducting a comprehensive evaluation of leading blind VQA (BVQA) models. Besides, we also created a new fusion-based BVQA model, which we dub the \textbf{VID}eo quality \textbf{EVAL}uator (VIDEVAL), that effectively balances the trade-off between performance and efficiency. Our experimental results show that VIDEVAL achieves state-of-the-art performance at a lower computational cost. We believe our reliable and reproducible benchmark will facilitate further research on deep learning-based BVQA modeling. An implementation of VIDEVAL has been made available online\footnote{\url{https://github.com/vztu/VIDEVAL_release}}.