帮摄影新手自动识别并移除照片杂乱元素，提升成片质量。
Clutter Detection and Removal by Multi-Objective Analysis for Photographic Guidance
- 基于美学评估区分物体贡献，定位干扰元素
- 结合生成对抗网络实现高分辨率图像修复
- 适合摄影初学者和需要快速优化构图的用户
照片中的杂乱元素会干扰摄影师传达情感或故事。由于缺乏经验或无意识疏忽，摄影新手常在画面中引入杂乱内容。为此，我们开发了一套相机引导系统，用于识别与消除杂乱。该系统通过估算并可视化各物体对整体美学与内容的贡献，帮助用户交互式识别干扰项，并提供清除建议及计算去杂工具。系统核心技术包括：基于美学评价的杂乱区分算法，以及基于生成对抗网络的迭代图像修复算法，可对高分辨率图像中被移除物体区域进行高质量重建。用户研究表明，本系统界面灵活、算法准确，使用户能更高效地识别干扰并拍摄出更高质量的照片。
原文摘要 · Abstract (English)
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.
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