We propose a simple yet effective image captioning framework that can determine the quality of an image and notify the user of the reasons for any flaws in the image. Our framework first determines the quality of images and then generates captions using only those images that are determined to be of high quality. The user is notified by the flaws feature to retake if image quality is low, and this cycle is repeated until the input image is deemed to be of high quality. As a component of the framework, we trained and evaluated a low-quality image detection model that simultaneously learns difficulty in recognizing images and individual flaws, and we demonstrated that our proposal can explain the reasons for flaws with a sufficient score. We also evaluated a dataset with low-quality images removed by our framework and found improved values for all four common metrics (e.g., BLEU-4, METEOR, ROUGE-L, CIDEr), confirming an improvement in general-purpose image captioning capability. Our framework would assist the visually impaired, who have difficulty judging image quality.

提出了一种简单而有效的图像字幕生成框架，该框架可以确定图像的质量并通知用户有关任何缺陷的原因。该框架通过训练和评估低质量图像检测模型，并尝试解释缺陷原因，从而提高了图像字幕的生成能力，对视力受损的人有帮助。

需要反馈以进行重拍：一种针对视障人士的可解释质量差图像提醒框架