  The current state-of-the-art methods for video corpus moment retrieval (VCMR)
often use similarity-based feature alignment approach for the sake of
convenience and speed. However, late fusion methods like cosine similarity
alignment are unable to make full use of the information from both query texts
and videos. In this paper, we combine feature alignment with feature fusion to
promote the performance on VCMR.
