CROSS-BATCH MEMORY FOR EMBEDDING LEARNING

摘要

This disclosure includes computer vision technologies, specifically for embeddings and metric learning. In various practical applications, such as product recognition, image retrieval, face recognition, etc., the disclosed technologies use a cross-batch memory mechanism to memorize prior embeddings, so that a pair-based learning model can mine more pairs across multiple mini-batches or even over the whole dataset. The disclosed technologies not only boost the performance for various applications, but considerably improve the computation itself with its memory-efficient approach.