With the prevalence of image editing techniques, users can create fantastic synthetic images, but the image quality may be compromised by the color/illumination discrepancy between the manipulated region and background. Inharmonious region localization aims to localize the inharmonious region in a synthetic image. In this work, we attempt to leverage auxiliary style feature to facilitate this task. Specifically, we propose a novel color mapping module and a style feature loss to extract discriminative style features containing task-relevant color/illumination information. Based on the extracted style features, we also propose a novel style voting module to guide the localization of inharmonious region. Moreover, we introduce semantic information into the style voting module to achieve further improvement. Our method surpasses the existing methods by a large margin on the benchmark dataset.
翻译:随着图像编辑技术的普及,用户可以制作惊人的合成图像,但图像质量可能因被操纵区域和背景之间的颜色/光化差异而受到影响。不协调的区域本地化旨在将不和谐的区域在合成图像中本地化。在这项工作中,我们试图利用辅助样式特征来推动这项任务。具体地说,我们提议了一个新的颜色绘图模块和一个风格特征损失,以提取含有任务相关颜色/光化信息的歧视性风格特征。根据提取的风格特征,我们还提议了一个创新风格投票模块,以指导不和谐区域的地方化。此外,我们把语义信息引入风格投票模块,以达到进一步的改进。我们的方法大大超过基准数据集的现有方法。