Inclusion of attention mechanism in the model helps to extract the most relevant objects or regions in the image [7, 8], which can be used for the generation of rich textual descriptions. These networks localize the salient regions in the images and produce improved image captions than previous works.
Feb 8, 2023
In this paper, we proposed a caption generation system combining a CNN-based object detection system and a language model with a recurrent neural network.
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What is the attention mechanism in image captioning?
What is the attention mechanism in image generation?
What is caption generation?
What is the methodology of image captioning?
Jun 3, 2022 · The attention mechanism learns a set of scoring weights that capture the relationship between the encoded vectors and the hidden state of the ...
An image captioning model combines convolutional and recurrent operations to produce a textual description of what is in the image, rather than a single label.
In this paper, we proposed a caption generation system combining a CNN-based object detection system and a language model with a recurrent neural network.
Feb 14, 2022 · This paper presents an attention-based, Encoder-Decoder deep architecture that makes use of convolutional features extracted from a CNN model pre-trained on ...
Nov 20, 2020 · The attention mechanism allows the neural network to have the ability to focus on its subset of inputs to select specific features.
Convolutional Neural Network (CNN) is used to generate visual attention after first deriving initial V3 features. The input texts for the associated images, on ...
Inspired by recent work in machine translation and object detection, we introduce an attention based model that automatically learns to describe.
The image captioning is utilized to develop the explanations of the sentences describing the series of scenes captured in the image or picture forms.