TIGEr: Text-to-Image Grounding for Image Caption Evaluation

IJCNLP 2019 Ming JiangQiuyuan HuangLei ZhangXin WangPengchuan ZhangZhe GanJana DiesnerJianfeng Gao

This paper presents a new metric called TIGEr for the automatic evaluation of image captioning systems. Popular metrics, such as BLEU and CIDEr, are based solely on text matching between reference captions and machine-generated captions, potentially leading to biased evaluations because references may not fully cover the image content and natural language is inherently ambiguous... (read more)

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