Cross Domain Retrieval

Cross-domain retrieval (CDR) aims to find similar items across different data types or domains, such as matching sketches to photographs or retrieving music based on textual descriptions. Current research emphasizes unsupervised and zero-shot approaches, focusing on techniques like semantic feature learning, multinomial blending for ranking, and synthetic data generation to address the challenges of limited labeled data and varying category spaces across domains. These advancements have significant implications for various applications, including multimedia search, personalized recommendations, and biometric identification systems, by enabling more robust and efficient retrieval across diverse data sources.