In this paper we revisit feature fusion, an old-fashioned topic, in the new context of text-to-
video retrieval. Different from previous research that considers feature fusion only at one …

In this paper we tackle the cross-modal video retrieval problem and, more specifically, we
focus on text-to-video retrieval. We investigate how to optimally combine multiple diverse …

Multimodal processing has attracted much attention lately especially with the success of pre-
training. However, the exploration has mainly focused on vision-language pre-training, as …

Negation is a common linguistic skill that allows human to express what we do NOT want.
Naturally, one might expect video retrieval to support natural-language queries with …

Ad-hoc Video Search (AVS) enables users to search for unlabeled video content using on-
the-fly textual queries. Current deep learning-based models for AVS are trained to optimize …

In this supplement, we provide more experimental results that are not included in the paper
due to space limit. Distribution of attentional weights per feature. We analyze the attentional …

In this paper, we summarize our TRECVID 2021 experiments. We participated in two tasks:
Ad-hoc Video Search (AVS) and Video-to-Text Description Generation (VTT). For the AVS …