<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si32.svg" display="inline" id="d1e1617"><mml:mrow><mml:msup><mml:mrow><mml:mi>M</mml:mi></mml:mrow><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msup><mml:mi>N</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:math>: Movement Enhancement with Multi-Relation toward Multi-Scale video representation for Temporal Action Detection-Reference-Cited by-同舟云学术

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M3Net: Movement Enhancement with Multi-Relation toward Multi-Scale video representation for Temporal Action Detection

Published:2024-11 Issue: Volume:155 Page:110702
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Zhao Zixuan,Wang Dongqi,Zhao Xu^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference40 articles.

1. Learning to refactor action and co-occurrence features for temporal action localization;Xia,2022

2. G-tad: Sub-graph localization for temporal action detection;Xu,2020

3. Graph convolutional networks for temporal action localization;Zeng,2019

4. A multi-modal transformer network for action detection;Korban;Pattern Recognit.,2023

5. Dual relation network for temporal action localization;Xia;Pattern Recognit.,2022

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