Corpus ID: 237941185

Deep Neural Networks for Blind Image Quality Assessment: Addressing the Data Challenge

@article{Athar2021DeepNN,
  title={Deep Neural Networks for Blind Image Quality Assessment: Addressing the Data Challenge},
  author={Shahrukh Athar and Zhongling Wang and Zhou Wang},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.12161}
}
The enormous space and diversity of natural images is usually represented by a few small-scale human-rated image quality assessment (IQA) datasets. This casts great challenges to deep neural network (DNN) based blind IQA (BIQA), which requires large-scale training data that is representative of the natural image distribution. It is extremely difficult to create human-rated IQA datasets composed of millions of images due to constraints of subjective testing. While a number of efforts have… Expand
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