Automatic image cropping is a method for maximizing the human-perceived quality of cropped regions in photographs. Although several works have proposed techniques for producing singular crops, little work has addressed the problem of producing multiple, distinct crops with aesthetic appeal. In this paper, we motivate the problem with a discussion on modern social media applications, introduce a dataset of 277 relevant images and human labels, and evaluate the efficacy of several single-crop models with an image partitioning algorithm as a pre-processing step. The dataset is available at https://github.com/RafeLoya/carousel.
翻译:自动图像裁剪是一种旨在最大化照片裁剪区域人类感知质量的方法。尽管已有若干研究提出了生成单一裁剪区域的技术,但针对生成多个具有美学吸引力的不同裁剪区域的问题,相关研究仍较为有限。本文通过探讨现代社交媒体应用的需求来阐述该问题的重要性,引入了一个包含277张相关图像及人工标注的数据集,并评估了结合图像分割算法作为预处理步骤的多种单裁剪模型的有效性。该数据集可通过 https://github.com/RafeLoya/carousel 获取。