Light Weight Image Super-Resolution with Adaptive Deep Residual Network
Keywords:
Single image super-resolution (SISR), AD residual network, Deep learningAbstract
The propose work is a single image super-resolution model based on Adaptive Deep Residual named as ADR-SR, which uses the Input Output Same Size (IOSS) structure and releases the dependence of up sampling layers compared with the existing SR methods. Specifically, the key element of our model is the Adaptive Residual Block (ARB), which replaces the commonly used constant factor with an adaptive residual factor. The experiments prove the effectiveness of our ADR-SR model, which can not only reconstruct images with better visual effects, but also get better objective performances.
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