This paper contributes to cross-lingual image annotation and retrieval in
terms of data and baseline methods. We propose COCO-CN, a novel dataset
enriching MS-COCO with manually written Chinese sentences and tags. For more
effective annotation acquisition, we develop a recommendation-assisted
collective annotation system, automatically providing an annotator with several
tags and sentences deemed to be relevant with respect to the pictorial content.
Having 20,342 images annotated with 27,218 Chinese sentences and 70,993 tags,
COCO-CN is currently the largest Chinese-English dataset that provides a
unified and challenging platform for cross-lingual image tagging, captioning
and retrieval. We develop conceptually simple yet effective methods per task
for learning from cross-lingual resources. Extensive experiments on the three
tasks justify the viability of the proposed dataset and methods. Data and code
are publicly available at this https URL

本文提出了 COCO-CN 数据集和推荐辅助集体注释系统，通过学习跨语言资源，完成了跨语言的图片标记、字幕和检索任务，为跨语言图像注释和检索领域做出了重要贡献。