A Novel Action Saliency and Context-Aware Network for Weakly-Supervised Temporal Action Localization
Author:
Affiliation:
1. Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, Tianjin, China
2. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China
Funder
National Natural Science Foundation of China
Young creative team in universities of Shandong Province
Jinan 20 projects in universities
Shandong Project towards the integration of education and industry
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Media Technology,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/6046/10016790/10007033.pdf?arnumber=10007033
Reference66 articles.
1. Soft-NMS — Improving Object Detection with One Line of Code
2. Deep Motion Prior for Weakly-Supervised Temporal Action Localization
3. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
4. Rethinking the Faster R-CNN Architecture for Temporal Action Localization
5. MAPLE: Masked Pseudo-Labeling autoEncoder for Semi-supervised Point Cloud Action Recognition
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