Partial Large Kernel CNNs for Efficient Super-Resolution

arXiv:2404.11848v1 Announce Type: new
Abstract: Recently, in the super-resolution (SR) domain, transformers have outperformed CNNs with fewer FLOPs and fewer parameters since they can deal with long-range dependency and adaptively adjust weights based on instance. In this paper, we demonstrate that CNNs, although less focused on in the current SR domain, surpass Transformers in direct efficiency measures. By incorporating the advantages of Transformers into CNNs, we aim to achieve both computational efficiency and enhanced performance. However, using a large kernel …

abstract arxiv cnns cs.cv current deal domain instance kernel paper parameters resolution transformers type