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Deep Distillation Recursive Network for Remote Sensing Imagery Super-Resolution.

, , , , , and . Remote. Sens., 10 (11): 1700 (2018)

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AIM 2019 Challenge on Video Extreme Super-Resolution: Methods and Results., , , , , , , , , and 12 other author(s). ICCV Workshops, page 3467-3475. IEEE, (2019)Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery., , , and . IEEE Trans. Computational Imaging, (2020)CDMMA: Coupled discriminant multi-manifold analysis for matching low-resolution face images., , , and . Signal Process., (2016)Two-step superresolution approach for surveillance face image through radial basis function-partial least squares regression and locality-induced sparse representation., , , , and . J. Electronic Imaging, 22 (4): 041120 (2013)DepthFormer: Exploiting Long-range Correlation and Local Information for Accurate Monocular Depth Estimation., , , and . Mach. Intell. Res., 20 (6): 837-854 (December 2023)Dynamic Association Learning of Self-Attention and Convolution in Image Restoration., , , , , and . CoRR, (2023)A Comprehensive Survey on 3D Content Generation., , , , , , , , , and 1 other author(s). CoRR, (2024)Transforming Image Super-Resolution: A ConvFormer-based Efficient Approach., , , and . CoRR, (2024)BaMBNet: A Blur-aware Multi-branch Network for Defocus Deblurring., , , and . CoRR, (2021)Low-Resolution and Low-Quality Face Super-Resolution in Monitoring Scene via Support-Driven Sparse Coding., , , and . J. Signal Process. Syst., 75 (3): 245-256 (2014)