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Image description task has been invariably examined in a static manner withqualitative presumptions held to be universally applicable, regardless of thescope or target of the description. In practice, however, different viewers maypay attention to different aspects of the image, and yield differentdescriptions or interpretations under various contexts. Such diversity inperspectives is difficult to derive with conventional image descriptiontechniques. In this paper, we propose a customized image narrative generationtask, in which the users are interactively engaged in the generation process byproviding answers to the questions. We further attempt to learn the user'sinterest via repeating such interactive stages, and to automatically reflectthe interest in descriptions for new images. Experimental results demonstratethat our model can generate a variety of descriptions from single image thatcover a wider range of topics than conventional models, while beingcustomizable to the target user of interaction.

Customized Image Narrative Generation via Interactive Visual Question Generation and Answering