VLSP 2021 - VieCap4H挑战:越南医疗保健领域的自动图像标题生成

Thao Minh Le, Long Hoang Dang, Thanh-Son Nguyen, Huyen Nguyen, Xuan-Son Vu
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引用次数: 7

摘要

本文介绍了VieCap4H,一个在越南医疗保健领域自动生成图像标题的大数据挑战。VieCap4H是第八届越南语言和语音处理年度研讨会(VLSP 2021)的一部分。该任务被视为图像字幕任务。给定一个静态图像,主要是关于医疗保健相关的场景,参与者被要求设计机器学习方法来生成越南语的自然语言字幕,以描述图像的视觉内容。我们介绍了VieCap4H,这是一个新的越南语人工注释图像标题数据集,包含从医疗保健领域的真实场景收集的10,000多个图像标题对。挑战参与者提出的所有模型都使用BLEU分数对基础事实进行评估。这个挑战是在AIHUB上进行的。VN平台。在不到两个月的时间里,这项挑战吸引了超过90名个人参与,并记录了900多份有效的参赛作品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VLSP 2021 - VieCap4H Challenge: Automatic Image Caption Generation for Healthcare Domain in Vietnamese
This paper presents VieCap4H, a grand data challenge on automatic image caption generation for the healthcare domain in Vietnamese. VieCap4H is held as part of the eighth annual workshop on VietnameseLanguage and Speech Processing (VLSP 2021). The task is considered as an image captioning task. Given a static image, mostly about healthcare-related scenarios, participants are asked to design machine learning methods to generate natural language captions in Vietnamese to describe the visual content of the image. We introduce VieCap4H, a novel human-annotated image captioning dataset in Vietnamese that contains over 10,000 image-caption pairs collected from real-world scenarios in the healthcare domain. All the models proposed by the challenge participants are evaluated using BLEU scores against groundtruths. The challenge was run on AIHUB.VN platform. Within less than two months, the challenge has attracted over 90 individual participants and recorded more than 900 valid submissions.  
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