ClassSR

2000년 도입 · 논문 1편에서 사용

ClassSR is a framework to accelerate super-resolution (SR) networks on large images (2K-8K). ClassSR combines classification and SR in a unified framework. In particular, it first uses a Class-Module to classify the sub-images into different classes according to restoration difficulties, then applies an SR-Module to perform SR for different classes. The Class-Module is a conventional classification network, while the SR-Module is a network container that consists of the to-be-accelerated SR network and its simplified versions.

출처: ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic

소개 논문: ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic