Multimodal Generation

Multimodal generation refers to the process of generating outputs that integrate multiple modalities (such as images, text, and sound) using deep learning models. These models are trained on data that includes various modalities, enabling them to produce results that synthesize different types of information. The goal of multimodal generation is to enhance the accuracy and comprehensiveness of the generated content. Its application value lies in its wide range of uses, including image captioning, text-to-image generation, and audio descriptions for video content, providing richer application scenarios for natural language processing.