multilingual cross-modal retrieval

Cross-lingual cross-modal retrieval is an important branch in the field of natural language processing, focusing on image-text matching and retrieval across different linguistic environments. This task aims to achieve precise associations between images and texts across languages through deep learning and multi-modal fusion technologies, thereby enhancing the efficiency and accuracy of multimedia information retrieval. Its application value is extensive, including but not limited to international social media analysis, multilingual visual question answering systems, and content recommendation services on a global scale.