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Given a video and its incomplete textural description with missing words, theVideo-Fill-in-the-Blank (ViFitB) task is to automatically find the missingword. The contextual information of the sentences are important to infer themissing words; the visual cues are even more crucial to get a more accurateinference. In this paper, we presents a new method which intuitively takesadvantage of the structure of the sentences and employs merging LSTMs (to mergetwo LSTMs) to tackle the problem with embedded textural and visual cues. In theexperiments, we have demonstrated the superior performance of the proposedmethod on the challenging "Movie Fill-in-the-Blank" dataset.

Video Fill in the Blank with Merging LSTMs