Abstract
Image captioning is a well-known task of generating textual description of a given image. Research work on this problem statement requires efforts in both computer vision and natural language processing domains to obtain better quality image descriptions. In this paper, we are proposing a new deep learning approach to generate image captions. In this approach, we generate a sequence of visual embeddings for objects and their relationships present in the image. These visual embeddings are arranged in a particular manner and are then supplied to the encoder part of an attention-based sequence-to-sequence model. In the final step, we receive the generated image captions from the decoder part of our sequence-to-sequence model. We tested its performance on MSCOCO Dataset, and the obtained results suggested that our model generates better image captions for MSCOCO testing dataset.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
