2017年全图像超分辨率挑战:数据集与研究

E. Agustsson, R. Timofte
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引用次数: 2070

摘要

本文介绍了一种新的基于示例的单图像超分辨率大型数据集,并研究了2017年NTIRE挑战赛中出现的最新技术。该挑战是同类挑战中的第一个,有6个比赛,数百名参与者和数十个提出的解决方案。本次挑战赛采用了我们新收集的多元2K分辨率图像数据集(DIV2K)。在我们的研究中,我们将挑战的解决方案与文献中的一组代表性方法进行了比较,并在我们提出的DIV2K数据集上使用不同的测量方法对它们进行了评估。此外,我们进行了一些实验,并就几个感兴趣的主题得出结论。我们的结论是,2017年的挑战赛推动了最先进的单图像超分辨率,在流行的Set5、Set14、B100、Urban100数据集和我们新提出的DIV2K数据集上取得了迄今为止最好的结果。
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NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study
This paper introduces a novel large dataset for example-based single image super-resolution and studies the state-of-the-art as emerged from the NTIRE 2017 challenge. The challenge is the first challenge of its kind, with 6 competitions, hundreds of participants and tens of proposed solutions. Our newly collected DIVerse 2K resolution image dataset (DIV2K) was employed by the challenge. In our study we compare the solutions from the challenge to a set of representative methods from the literature and evaluate them using diverse measures on our proposed DIV2K dataset. Moreover, we conduct a number of experiments and draw conclusions on several topics of interest. We conclude that the NTIRE 2017 challenge pushes the state-of-the-art in single-image super-resolution, reaching the best results to date on the popular Set5, Set14, B100, Urban100 datasets and on our newly proposed DIV2K.
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