Adaptive Residual Correction Network for Efficient Single Image Super-Resolution
This work revisits CNN-based residual learning for SISR and proposes an adaptive residual correction network (AdaRCN), a residual correction mechanism that adaptively compensates for the bias in the residual, which is utilized to ease error accumulation and improve mapping accuracy.