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-1.3
Paper Title CURIOUSLY EFFECTIVE FEATURES FOR IMAGE QUALITY PREDICTION
Authors Sören Becker, Thomas Wiegand, Sebastian Bosse, Fraunhofer Heinrich Hertz Institute, Germany
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 The performance of visual quality prediction models is commonly assumed to be closely tied to their ability to capture perceptually relevant image aspects. Models are thus either based on sophisticated feature extractors carefully designed from extensive domain knowledge or optimized through feature learning. In contrast to this, we find feature extractors constructed from random noise to be sufficient to learn a linear regression model whose quality predictions reach high correlations with human visual quality ratings, on par with a model with learned features. We analyze this curious result and show that besides the quality of feature extractors also their quantity plays a crucial role - with top performances only being achieved in highly overparameterized models.