Xiangyang Kong

POGA: Paraphrased and Oppositional Graph Alignment for Fine-Grained Cross-Modal Retrieval

Most of the models used to generate embeddings for retrieval are not trained for the purpose which leads them to focus on coarse semantic alignment rather than particular object attributes or arrangements. This limits their performance, particularly on challenging problems such as cross-modal fine-g