Revisiting image captioning via maximum discrepancy competition

Boyang Wan, Wenhui Jiang, Yuming Fang, Minwei Zhu, Qin Li, Yang Liu

Abstract: Highlights•We propose a new model comparison method without an unaffordable large-scale subjective annotation experiment.•A new similarity function named NGSM is proposed as a semantic distance measure to model discrepancy of captions. With this NGSM, the informative images can be selected effectively from an arbitrary large-scale raw image dataset.•We demonstrate quantitative results of the generalization ability of the competing ICMs and provide detailed analysis about the key factor of improving the generalization ability of ICMs.