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 …

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

The rapid growth of user-generated videos on the Internet has intensified the need for text-
based video retrieval systems. Traditional methods mainly favor the concept-based …

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 …

Video-text retrieval is an important yet challenging task in vision-language understanding,
which aims to learn a joint embedding space where related video and text instances are …

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 …

In recent years, the growing demand for medical imaging diagnosis has placed a significant
burden on radiologists. As a solution, Medical Vision-Language Pre-training (Med-VLP) …

Ranking models are the main components of information retrieval systems. Several
approaches to ranking are based on traditional machine learning algorithms using a set of …