Hierarchical Local-Global Transformer for Temporal Sentence Grounding

Understand

This paper studies the multimedia problem of temporal sentence grounding (TSG), which aims to accurately determine the specific video segment in an untrimmed video according to a given sentence query.

• Traditional TSG methods mainly follow the top-down or bottom-up framework and are not end-to-end.
• They severely rely on time-consuming post-processing to refine the grounding results.
• Recently, some transformer-based approaches are proposed to efficiently and effectively model the fine-grained semantic alignment between video and query.