DRN uses residual distilling blocks (RDB) and groups (RDG) to achieve a better performance to model size trade-off in single image super-resolution than existing methods.
Network Architecture As shown in Fig.3, the proposed DRN mainly consists three parts: low-level feature extraction(LFE), residual disti lling groups(RDGs), image reconstruction(IR)
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Distilling with Residual Network for Single Image Super Resolution
DRN uses residual distilling blocks (RDB) and groups (RDG) to achieve a better performance to model size trade-off in single image super-resolution than existing methods.