Real-BlindSR Dataset

Citation Author(s):
GuangYong
Chen
WuDing
Weng
JianNan
Su
Min
Gan
C. L. Philip
Chen
Submitted by:
Jian-Nan Su
Last updated:
Sun, 07/16/2023 - 22:46
DOI:
10.21227/z2yz-c641
License:
75 Views
Categories:
Keywords:
0
0 ratings - Please login to submit your rating.

Abstract 

Realistic benchmark datasets are crucial for providing a consistent measurement baseline for comparing different BlindSR methods and testing their generalization ability in real-world scenarios. However, the evaluation of BlindSR methods is still limited by the lack of a common dataset that conforms to realistic degradation scenarios. We construct a benchmark dataset that follows real scenarios, which reflects the real-world BlindSR problem more accurately than existing synthetic datasets. The Real-BlindSR dataset includes diverse degradation types frequently observed in realistic situations, such as different downsampling scales. This dataset offers a comprehensive and realistic benchmark for assessing the performance of BlindSR methods.The Real-BlindSR Dataset we built is mainly used to evaluate the BlindSR task, which includes LR-HR paired images of three different scales of X2, X4, and X8, and includes compression from different Internet platforms and processing of real-world degradation three different tracks.

Instructions: 

This dataset offers a comprehensive and realistic benchmark for assessing the performance of BlindSR methods.The Real-BlindSR Dataset we built is mainly used to evaluate the BlindSR task, which includes LR-HR paired images of three different scales of X2, X4, and X8, and includes compression from different Internet platforms and processing of real-world degradation three different tracks.

Dataset Files

    Files have not been uploaded for this dataset