TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals

Understand

Temporal Action Proposal (TAP) generation is an important problem, as fast and accurate extraction of semantically important (e.g.

• human actions) segments from untrimmed videos is an important step for large-scale video analysis.
• We propose a novel Temporal Unit Regression Network (TURN) model.
• There are two salient aspects of TURN: (1) TURN jointly predicts action proposals and refines the temporal boundaries by temporal coordinate regression; (2) Fast computation is enabled by unit feature reuse: a long untrimmed video is decomposed into video units, which are reused as basic building blocks of temporal proposals.