As many previous works, the encoder-decoder framework is adopted in our proposed model, in which the encoder is responsible for encoding the region proposal features and extracting global caption feature based on a specially designed module of predicting the caption objects, and the decoder generates captions by taking the obtained global caption feature along with the encoded visual features as inputs for each attention head of the decoder layer. In this paper, we develop a novel global-attention-based neural network (GANN) for vision language intelligence, specifically, image captioning (language description of a given image).
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