Blind Stereoscopic Image Quality Assessment By Deep Neural Network Of Multi-Level Feature Fusion
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/9099125/9102711/09102888.pdf?arnumber=9102888
Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Are Standard CNNs Good Enough for No-Reference Stereoscopic Image Quality Assessment?;2024 International Conference on Signal Processing and Communications (SPCOM);2024-07-01
2. Perceptual Quality Assessment of Omnidirectional Images: A Benchmark and Computational Model;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-03-08
3. A No-Reference Stereoscopic Image Quality Assessment Based on Cartoon Texture Decomposition and Human Visual System;Communications in Computer and Information Science;2024
4. Multilevel Feature Fusion for End-to-End Blind Image Quality Assessment;IEEE Transactions on Broadcasting;2023-09
5. 3D reconstruction quality assessment using 2D reprojection with dynamic partitioning;The Imaging Science Journal;2023-08-24
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