Learning 2D Temporal Adjacent Networks for Moment Localization with Natural Language

Understand

We address the problem of retrieving a specific moment from an untrimmed video by a query sentence.

• This is a challenging problem because a target moment may take place in relations to other temporal moments in the untrimmed video.
• Existing methods cannot tackle this challenge well since they consider temporal moments individually and neglect the temporal dependencies.
• In this paper, we model the temporal relations between video moments by a two-dimensional map, where one dimension indicates the starting time of a moment and the other indicates the end time.