Embracing Uncertainty: Decoupling and De-bias for Robust Temporal Grounding

Understand

Temporal grounding aims to localize temporal boundaries within untrimmed videos by language queries, but it faces the challenge of two types of inevitable human uncertainties: query uncertainty and label uncertainty.

• The two uncertainties stem from human subjectivity, leading to limited generalization ability of temporal grounding.
• In this work, we propose a novel DeNet (Decoupling and De-bias) to embrace human uncertainty: Decoupling - We explicitly disentangle each query into a relation feature and a modified feature.
• The relation feature, which is mainly based on skeleton-like words (including nouns and verbs), aims to extract basic and consistent information in the presence of query uncertainty.