Optimization of Module Transferability in Single Image Super-Resolution: Universality Assessment and Cycle Residual Blocks
arXiv · · Significant research
Summary
This paper introduces a method for quantifying the transferability of architectural components in Single Image Super-Resolution (SISR) models, termed "Universality," and proposes a Universality Assessment Equation (UAE). Guided by the UAE, the authors design optimized modules, Cycle Residual Block (CRB) and Depth-Wise Cycle Residual Block (DCRB), and demonstrate their effectiveness across various datasets and low-level tasks. Results show that networks using these modules outperform state-of-the-art methods, achieving improved PSNR or parameter reduction.
Keywords
Single Image Super-Resolution · module transferability · Universality Assessment Equation · Cycle Residual Block · deep learning
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