Image Description using Attention Mechanism
International Journal of Recent Technology and Engineering (IJRTE) · 2019
Image Description involves generating a textual description of images which is essential for the problem of image understanding. The variable and ambiguous nature of possible image descriptions make this task challenging. There are different approaches for automated image captioning which explain the image contents along with a complete understanding of the image, rather than just simply classifying it into a particular object type. However, learning image contexts from the text and generating image descriptions similar to human's description requires to focus on important features of the image using attention mechanism. We provide an outline of the various recent works in image description models employing various attention mechanism. We present an analysis of the various approaches, datasets and evaluation metrics that are utilized for image description. We showcase a model using the encoder-decoder attention mechanism based on Flickr dataset and evaluate the performance using BLEU metrics.