Enhancing Multimodal Understanding with CLIP-Based Image-to-Text Transformation

Abstract

The process of transforming input images into corresponding textual explanations stands as a crucial and complex endeavor within the domains of computer vision and natural language processing. In this paper, we propose an innovative ensemble approach that harnesses the capabilities of Contrastive Language-Image Pretraining models

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