论文标题
互动肖像协调
Interactive Portrait Harmonization
论文作者
论文摘要
当前的图像协调方法将整个背景视为协调的指导。但是,这可能会限制用户在后台选择任何特定对象/人员以指导协调的能力。为了启用用户与协调之间的灵活交互,我们引入了交互式协调,这是一种新的设置,在该设置中,在参考图像而不是整个背景中相对于所选\ emph {region}进行协调。提出了一个新的灵活框架,允许用户选择背景图像的某些区域并使用它来指导协调。受专业人像协调用户的启发,我们还引入了新的亮度匹配损失,以最佳匹配复合前景和选择参考区域之间的颜色/亮度条件。该框架为图像协调管道提供了更多控制,从而实现了视觉令人愉悦的肖像编辑。此外,我们还介绍了一个经过精心策划的新数据集,以验证肖像协调。对合成和现实世界数据集进行的广泛实验表明,与以前的协调基线相比,所提出的方法是有效而健壮的,尤其是对于肖像画。 \ href {https://jeya-maria-jose.github.io/iph-web/}的项目网页{https://jeya-maria-jose.github.io/iph-web/}
Current image harmonization methods consider the entire background as the guidance for harmonization. However, this may limit the capability for user to choose any specific object/person in the background to guide the harmonization. To enable flexible interaction between user and harmonization, we introduce interactive harmonization, a new setting where the harmonization is performed with respect to a selected \emph{region} in the reference image instead of the entire background. A new flexible framework that allows users to pick certain regions of the background image and use it to guide the harmonization is proposed. Inspired by professional portrait harmonization users, we also introduce a new luminance matching loss to optimally match the color/luminance conditions between the composite foreground and select reference region. This framework provides more control to the image harmonization pipeline achieving visually pleasing portrait edits. Furthermore, we also introduce a new dataset carefully curated for validating portrait harmonization. Extensive experiments on both synthetic and real-world datasets show that the proposed approach is efficient and robust compared to previous harmonization baselines, especially for portraits. Project Webpage at \href{https://jeya-maria-jose.github.io/IPH-web/}{https://jeya-maria-jose.github.io/IPH-web/}