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The Best of Both Worlds: a Framework for Combining Degradation Prediction with High Performance Super-Resolution Networks.

, , , , , and . CoRR, (2022)

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Forensic Face Photo-Sketch Recognition Using a Deep Learning-Based Architecture., and . IEEE Signal Process. Lett., 24 (11): 1586-1590 (2017)The Best of Both Worlds: a Framework for Combining Degradation Prediction with High Performance Super-Resolution Networks., , , , , and . CoRR, (2022)A Large-Scale Software-Generated Face Composite Sketch Database., and . BIOSIG, volume P-260 of LNI, page 217-224. GI / IEEE, (2016)Comments on "Domain Alignment Embedding Network for Sketch Face Recognition".. IEEE Access, (2022)Denoising of 3D Point Clouds Constructed from Light Fields., and . ICASSP, page 1882-1886. IEEE, (2019)Face photo-sketch recognition using local and global texture descriptors., and . EUSIPCO, page 2240-2244. IEEE, (2016)Improving Super-Resolution Performance using Meta-Attention Layers., , , , and . CoRR, (2021)Super Resolution of Light Field Images Using Linear Subspace Projection of Patch-Volumes., , and . IEEE J. Sel. Top. Signal Process., 11 (7): 1058-1071 (2017)The Best of Both Worlds: A Framework for Combining Degradation Prediction with High Performance Super-Resolution Networks., , , , , and . Sensors, 23 (1): 419 (2023)A no-reference video quality metric using a Natural Video Statistical Model., and . EUROCON, page 1-6. IEEE, (2015)