Described herein are systems and methods that exploit hierarchical Recurrent Neural Networks (RNNs) to tackle the video captioning problem; that is, generating one or multiple sentences to describe a realistic video. Embodiments of the hierarchical framework comprise a sentence generator and a paragraph generator. In embodiments, the sentence generator produces one simple short sentence that describes a specific short video interval. In embodiments, it exploits both temporal- and spatial-attention mechanisms to selectively focus on visual elements during generation. In embodiments, the paragraph generator captures the inter-sentence dependency by taking as input the sentential embedding produced by the sentence generator, combining it with the paragraph history, and outputting the new initial state for the sentence generator.
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