Inharmonious region localization aims to localize the region in a synthetic image which is incompatible with surrounding background. The inharmony issue is mainly attributed to the color and illumination inconsistency produced by image editing techniques. In this work, we tend to transform the input image to another color space to magnify the domain discrepancy between inharmonious region and background, so that the model can identify the inharmonious region more easily. To this end, we present a novel framework consisting of a color mapping module and an inharmonious region localization network, in which the former is equipped with a novel domain discrepancy magnification loss and the latter could be an arbitrary localization network. Extensive experiments on image harmonization dataset show the superiority of our designed framework. Our code is available at https://github.com/bcmi/MadisNet-Inharmonious-Region-Localization.
翻译:无协调的区域本地化旨在将该区域定位为与周围背景不相容的合成图像,和谐问题主要归因于图像编辑技术产生的颜色和照明不一致。在这项工作中,我们倾向于将输入图像转换为另一个颜色空间,以放大不和谐区域和背景之间的域差异,以便模型更容易地识别不和谐区域。为此,我们提出了一个由颜色绘图模块和不和谐区域本地化网络组成的新框架,前者拥有新的域差异放大损失,后者可能是任意的本地化网络。关于图像统一数据集的广泛实验显示了我们设计框架的优越性。我们的代码可在https://github.com/bcmi/MadidisNet-Inharmonorious-Region-本地化网站上查阅。