Title
Coco-Cn For Cross-Lingual Image Tagging, Captioning, And Retrieval
Abstract
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 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 https://github.com/li-xirong/coco-cn.
Year
DOI
Venue
2019
10.1109/TMM.2019.2896494
IEEE TRANSACTIONS ON MULTIMEDIA
Keywords
Field
DocType
COCO-CN, Chinese language, cross-lingual learning, image tagging, image captioning, image retrieval
Closed captioning,Cross lingual,Automatic image annotation,Annotation,Task analysis,Pattern recognition,Visualization,Computer science,Image retrieval,Natural language processing,Artificial intelligence,The Internet
Journal
Volume
Issue
ISSN
21
9
1520-9210
Citations 
PageRank 
References 
3
0.40
0
Authors
7
Name
Order
Citations
PageRank
Xirong Li1119168.62
Chaoxi Xu2294.63
Xiaoxu Wang330.40
Weiyu Lan4734.33
Zhengxiong Jia530.40
Gang Yang65315.64
Jieping Xu741.77