Embarrassingly Simple Model for Early Action Proposal
Marcos Baptista-R\'ios, Roberto J. L\'opez-Sastre, Franciso Javier, Acevedo-Rodr\'iguez, Saturnino Maldonado-Basc\'on

TL;DR
This paper introduces a simple, classifier-based 3D CNN model for real-time early action proposal in videos, outperforming more complex existing methods in online scenarios.
Contribution
The paper presents a straightforward 3D CNN approach for online action proposal, emphasizing simplicity and improved performance over complex prior methods.
Findings
Outperforms state-of-the-art methods in early action proposal
Uses standard 3D CNNs for online detection
Achieves significant improvements in real-time scenarios
Abstract
Early action proposal consists in generating high quality candidate temporal segments that are likely to contain an action in a video stream, as soon as they happen. Many sophisticated approaches have been proposed for the action proposal problem but from the off-line perspective. On the contrary, we focus on the on-line version of the problem, proposing a simple classifier-based model, using standard 3D CNNs, that performs significantly better than the state of the art.
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Taxonomy
TopicsAdvanced Vision and Imaging · Human Pose and Action Recognition · Video Analysis and Summarization
