A Survey on Image Captioning Using Object Detection and NLP

Abstract

Recent years have seen the emergence of image captioning as a revolutionary technical development that seamlessly blends computer vision and natural language processing. The integration of various domains facilitates the production of captivating captions for pictures, promoting a more profound comprehension of visual material. This study offers a thorough analysis of the rapidly developing field of image captioning, examining its uses in various settings such as social media, online platforms, assistive technology, and content indexing. It emphasizes the critical importance of advanced techniques like You Only Look Once (YOLO) for accurate item detection and Natural Language Processing (NLP) for creating subtle captions. While NLP gives the resulting text a layer of contextual depth, YOLO guarantees precise object detection, which helps with caption accuracy. Using these cutting-edge methods boosts the overall efficacy of image captioning systems and represents a noteworthy trend in the literature. Examining the evolution of image captioning, the review paper highlights how important it is for multimodal comprehension. Image captioning is a transformative tool that enhances the readability of visual content and influences contemporary digital experiences in various contexts. The development of image captioning is summarized in this abstract, which also highlights the tendency to use cutting-edge techniques for more accurate and nuanced caption production.