Global Two-Stream Network for Temporal Action Proposal Generation

Abstract

Temporal action detection is a practical but challenging task. The current temporal action detection task has major shortcomings in the accuracy of proposal generation. The extraction of long-range temporal information features and the fusion of two-stream features for the task of temporal action proposal generation are still a challenge that needs to be improved. In this paper, we propose the Global Two-Stream Network, which innovatively introduces the Non-Local operation to extract the global background information from the features of the generated candidate proposals. And the backbone network of two-streams is used for better utilization of two-stream features to generate temporal action proposal segments with precise bounds and high confidence.