Temporal Grounding is to identify specific moments or highlights from a video corresponding
to textual descriptions. Typical approaches in temporal grounding treat all video clips …

Sign language video retrieval plays a key role in facilitating information access for the deaf
community. Despite significant advances in video-text retrieval, the complexity and inherent …

We present LLoVi, a language-based framework for long-range video question-answering
(LVQA). Unlike prior long-range video understanding methods, which are often costly and …

Most text-video retrieval methods utilize the text-image pre-trained CLIP as a backbone,
incorporating complex modules that result in high computational overhead. As a result …

Text-Video Retrieval (TVR) aims to align and associate relevant video content with
corresponding natural language queries. Most existing TVR methods are based on large …

Existing video-text retrieval methods predominantly focus on designing diverse cross-modal
interaction mechanisms between captions and videos. However, those approaches diverge …

Different from traditional video retrieval, sign language retrieval is more biased towards
understanding the semantic information of human actions contained in video clips. Previous …

Locating specific moments within long videos (20–120 min) presents a significant challenge,
akin to finding a needle in a haystack. Adapting existing short video (5–30 s) grounding …

Abstract Recent Audio-Text Retrieval (ATR) models have achieved progressive results,
which pursue semantic interaction upon audio and text pairs. To clarify this coarse-grained …

In this work, we propose an efficient Video-Language Alignment (ViLA) network. Our ViLA
model addresses both efficient frame sampling and effective cross-modal alignment in a …