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Attribute|driven Attention Model for Image Captioning


Attribute-driven Attention Model for Image Captioning - IJCAI

The uniqueness of our infer- ence model lies in the usage of a RNN with the visual attention mechanism to observe the image before generating captions.

Attribute-driven Attention Model for Image Captioning - IJCAI

The uniqueness of our inference model lies in the usage of a RNN with the visual attention mechanism to \textit{observe} the image before generating captions.

Attribute-driven Attention Model for Image Captioning

This paper focuses on training a good attribute-inference model via the recurrent neural network (RNN) for image captioning, where the co-occurrence ...

Attribute-driven Attention Model for Image Captioning - ResearchGate

Abstract. Despite the fact that attribute-based approaches and attention-based approaches have been proven to be effective in image captioning, most attribute- ...

An image caption model based on attention mechanism and deep ...

In order to further improve the performance of our image caption model, this study incorporates an attention mechanism to focus details and constructs a double- ...

Show, observe and tell: attribute-driven attention model for image ...

Most attention-based captioning models directly leverage the feature map extracted from CNN, in which many features may be redundant in relation to the image ...

Attribute-driven image captioning via soft-switch pointer

Yan et al. [13] proposed a task-adaptive attention model which decides whether to believe in visual content or non-visual clues for predicting different words.

Image Captioning with Attention | dida blog

An image caption generation model generally works as follows: it takes an image as input, identifies its relevant parts, and generates textual ...

Gourang97/attention-based-image-captioning - GitHub

We can understand that there is one additional layer from the classic architecture, and this new layer makes the model as attention model. While predicting the ...

An image caption model based on attention mechanism and deep ...

In recent years, the performance of image caption has been significantly enhanced with the introduction of encoder-decoder architecture in ...

Boosting Image Captioning With Attributes - CVF Open Access

attributes to model semantic attention to the locally previ- ous words, as opposed to holistically employing attributes as a kind of complementary ...

Text-Guided Attention Model for Image Captioning

On the other hand, image attributes are learned and the presence of the attributes, instead of an encoded image feature, is given to LSTM as an input to ...

Image captioning model using attention and object features to mimic ...

One of the most successful methods for image captioning is implementing an Encoder-Decoder architecture. It encodes images to a high-level ...

AIC-AB NET: A Neural Network for Image Captioning with Spatial ...

For caption generation, adaptive spatial attention determines which image region best represents the image and whether to attend to the visual ...

Image Captioning and Tagging Using Deep Learning Models

AI-driven image tagging and description use cases · Researching Deep Learning models for Image Captioning · Up-Down attention model for image ...

RefCap: image captioning with referent objects attributes - Nature

proposed the attention mechanism, allowing the model to selectively focus on different image regions while generating captions. Similarly, Lu et ...

Attention-guided image captioning with adaptive global and local ...

Image captioning which combines visual object recognition with language models has been drawing increasing interests in computer vision and image understanding ...

Image Captioning with Attribute Refinement - IEEE Xplore

Abstract: Semantic attention has long been adopted to image captioning models to enhance the image captioning performances. The models pre-trained for ...

Attention Mechanism For Image Caption Generation in Python

It helps to pay attention to the most relevant information in the source sequence. The model predicts a target word based on the context vectors ...

Leveraging Human Attention for Image Captioning

Visual attention has shown usefulness in image captioning, with the goal of enabling a caption model to selectively focus on regions of interest.