Real-Time Image and Video Captioning Using Advanced Deep Learning Models

Descriptive captions generated for images and videos by machines in the contemporary world has been of much essence. This paper introduces a method of real-time image as well as video captioning using a recent advancement in deep learning models combining CNNs for feature extraction and RNNs for sequence generation. The hybrid model with integrated attention mechanisms enhance contextual understanding as well as better quality caption generation. Our results establish signif- icant improvements toward captioning accuracy and relevance over existing methods on standard datasets. Finally, with real- time capabilities, such systems can have various applications in accessibility, content creation, and automation in social media. In that regard, the obtained results suggest that our methodology could really fill the gap between the visual content and natural language understanding and introduce an important step for more intuitive human-computer interaction.