Attention Beam: An Image Captioning Approach (Student Abstract)
Keywords:Image Captioning, Beam Search, Attention Network, Natural Language Generation, Computer Vision
AbstractThe aim of image captioning is to generate textual description of a given image. Though seemingly an easy task for humans, it is challenging for machines as it requires the ability to comprehend the image (computer vision) and consequently generate a human-like description for the image (natural language understanding). In recent times, encoder-decoder based architectures have achieved state-of-the-art results for image captioning. Here, we present a heuristic of beam search on top of the encoder-decoder based architecture that gives better quality captions on three benchmark datasets: Flickr8k, Flickr30k and MS COCO.
How to Cite
Shrimal, A., & Chakraborty, T. (2021). Attention Beam: An Image Captioning Approach (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15887-15888. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17940
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