A vision-language model is a type of artificial intelligence that integrates visual information (images or videos) with textual information (language) to perform various tasks that require understanding and processing both modalities. These models are designed to bridge the gap between computer vision and natural language processing, enabling machines to interpret and generate content that involves both images and text. Vision-language models represent a significant advancement in computer vision research, enabling machines to better understand and interact with the world through a combination of visual and textual information.
In this seminar, we will briefly explain the key components of these models and explore how they are being used and achieving significant advancements in recent computer vision research.