This paper attacks the challenging problem of video retrieval by text. In such a retrieval
paradigm, an end user searches for unlabeled videos by ad-hoc queries described …

Ad-hoc video search (AVS) is an important yet challenging problem in multimedia retrieval.
Different from previous concept-based methods, we propose a fully deep learning method …

Cross-modal retrieval between videos and texts has gained increasing interest because of
the rapid emergence of videos on the web. Generally, a video contains rich instance and …

Research in the Vision and Language area encompasses challenging topics that seek to
connect visual and textual information. When the visual information is related to videos, this …

Retrieving unlabeled videos by textual queries, known as Ad-hoc Video Search (AVS), is a
core theme in multimedia data management and retrieval. The success of AVS counts on …

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 …

We study the task of robust feature representations, aiming to generalize well on multiple
datasets for action recognition. We build our method on Transformers for its efficacy …

Action Spotting in the broadcast soccer game is important to understand salient actions and
video summary applications. In this paper, we propose an efficient transformer-based …

Abstract We propose an Efficient Activity Detection System, Argus, for Extended Video
Analysis in the surveillance scenario. For the spatial-temporal event detection in the …

Answering query with semantic concepts has long been the mainstream approach for video
search. Until recently, its performance is surpassed by concept-free approach, which …