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An Effective Dense Co-Attention Networks for Visual Question Answering
2020
Sensors
At present, the state-of-the-art approaches of Visual Question Answering (VQA) mainly use the co-attention model to relate each visual object with text objects, which can achieve the coarse interactions between multimodalities. However, they ignore the dense self-attention within question modality. In order to solve this problem and improve the accuracy of VQA tasks, in the present paper, an effective Dense Co-Attention Networks (DCAN) is proposed. First, to better capture the relationship
doi:10.3390/s20174897
pmid:32872620
fatcat:6hp4hzru5jggtgescdtv635b5e