In this paper, we propose a sequence-to-sequence deep learning model to address the news image caption generation problem.
we first encode each sentence of a given news article using an order-embedding vector and extract semantic features from the accompanying image using a pre-trained CNN Network, which are further projected to same semantic space, such that both text and image vectors reside in a common semantic space (Vendrov et al., 2015).