Multi-dataset learning with channel modulation loss for blind image quality assessment
Author:
Funder
National Key R &D Program of China
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-18542-z.pdf
Reference60 articles.
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2. Hou J, Lin W, Zhao B (2020) Content-dependency reduction with multi-task learning in blind stitched panoramic image quality assessment. In: Proceedings international conference image processing, IEEE, pp 3463–3467
3. Li L, Zhou Y, Gu K, Lin W, Wang S (2017) Quality assessment of dibr-synthesized images by measuring local geometric distortions and global sharpness. IEEE Trans Multimedia 20(4):914–926
4. Jiang Q, Shao F, Lin W, Jiang G (2017) Blique-tmi: Blind quality evaluator for tone-mapped images based on local and global feature analyses. IEEE Trans Circuits Syst Video Technol 29(2):323–335
5. Kim W, Nguyen A-D, Lee S, Bovik AC (2020) Dynamic receptive field generation for full-reference image quality assessment. IEEE Trans Image Process 29:4219–4231
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