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[Paper] DeepBIQ: Deep Learning for Blind IQA (Image Quality Assessment)
Examples from the LIVE In the Wild IQ Chall. DB
In this story, On the use of deep learning for blind image quality assessment (DeepBIQ), by University of Milano-Bicocca, is presented. I read this because I recently study IQA/VQA. In this paper:
Features of subregions are extracted by fine-tuned convolutional neural networks (CNNs) as a generic image description, then input to SVR to regress the image quality scores.
as a generic image description, then input to SVR to regress the image quality scores. The image quality is estimated by average-pooling the scores predicted on multiple subregions of the original image.
of the original image. This proposed approach is named DeepBIQ.
This is a paper in 2017 Springer JSVIP (Signal, Image and Video Processing). (Sik-Ho Tsang @ Medium)
