Abstract
Clutter in photos is a distraction preventing photographers from conveying the intended emotions or stories to the audience. Photography amateurs frequently include clutter in their photos due to unconscious negligence or the lack of experience in creating a decluttered, aesthetically appealing scene for shooting. We are thus motivated to develop a camera guidance system that provides solutions and guidance for clutter identification and removal. We estimate and visualize the contribution of objects to the overall aesthetics and content of a photo, based on which users can interactively identify clutter. Suggestions on getting rid of clutter, as well as a tool that removes cluttered objects computationally, are provided to guide users to deal with different kinds of clutter and improve their photographic work. Two technical novelties underpin interactions in our system: a clutter distinguishment algorithm with aesthetics evaluations for objects and an iterative image inpainting algorithm based on generative adversarial nets that reconstructs missing regions of removed objects for high-resolution images. User studies demonstrate that our system provides flexible interfaces and accurate algorithms that allow users to better identify distractions and take higher quality images within less time.
Abstract (translated)
照片中的杂乱是妨碍摄影师向观众传达意图情感或故事的障碍。摄影初学者常常因为无意识的疏忽或缺乏创建整洁、美观拍摄场景的经验而将杂物纳入照片中。因此，我们致力于开发一个相机引导系统，为用户提供解决和指导杂乱识别与去除的方法。该系统基于对物体在整体美学和内容中的贡献进行估计和可视化，帮助用户交互式地识别杂物，并提供有关如何消除杂乱的建议以及一种通过计算移除杂乱对象的工具，从而引导用户处理不同类型的杂乱并改进他们的摄影作品。 我们系统的两个技术亮点支持了这些互动：一个具有美学评估功能的杂物区分算法和基于生成对抗网络（GAN）的迭代图像修复算法。后者用于重建被删除物体后的缺失区域，适用于高分辨率图片。用户体验研究表明，我们的系统提供了灵活的界面和准确的算法，使用户能够更有效地识别干扰因素，并在较短的时间内拍摄出更高品质的照片。
URL
https://arxiv.org/abs/2507.14553
