Residual block-based complexity-aware neural ODE fusion for image super-resolution
This paper proposes Adaptive ODE-ResNet (Adaptive ODE-ResNet), which reconstructs the residual block into a continuous ODE-driven process to realize flexible and accurate feature evolution and provides an accurate, efficient and scalable continuous-time modeling scheme for high-resolution image reconstruction.