Enhancing Multimodal Understanding with CLIP-Based Image-to-Text
  Transformation
Chang Che Qunwei Lin Xinyu Zhao Jiaxin Huang Liqiang Yu
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.