… In this paper, we propose a new image captioning ap… attention model. Please refer to Figure
1 for an overview of our algorithm. Our definition for semantic attention in image captioning …

… visual attention. This exemplar-based attention model is learned within our image captioning
ar… -based scheme to learn attention using multiple exemplar guidance captions. This avoids …

… deep learning models for image captioning. Instead of offering a … deep image captioning
models, we explain various types of attention mechanisms used for the task of image captioning …

… “attention gate” using the attention result and the current context, then adds another attention
… We apply AoA to both the encoder and the decoder of our image captioning model, which …

… For other tasks with complex inputs, such as image captioning, the notion of parts is less …
novel attention model and three different ways to select parts of the image, or areas of attention, …

… In this paper, we propose a Hierarchical Attention Network (HAN) for image captioning. The
key of our work is adopting semantically weak patch features, semantically moderate object …

… attention mechanism for image captioning. In this paper, we introduce a unified attention
block — X-Linear attention … Technically, X-Linear attention block simultaneously exploits both …

… a bottom-up attention model in Section 3.1. In Section 3.2 we outline the architecture of our
image captioning model and in Section 3.3 we outline our VQA model. We note that for the top…

… in relation to the image content. In this … attention model for image captioning. We focus
on training a good attribute-inference model via the recurrent neural network (RNN) for image …

… in human attention during free-viewing and image captioning tasks. … attention deployment
mechanisms in the top-down soft attention approach that is argued to mimic human attention …