MV-TAL: Mulit-view Temporal Action Localization in Naturalistic Driving-Reference-Cited by-同舟云学术

MV-TAL: Mulit-view Temporal Action Localization in Naturalistic Driving

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Author:

Li Wei¹,Chen Shimin¹,Gu Jianyang¹,Wang Ning¹,Chen Chen¹,Guo Yandong¹

Affiliation:

1. OPPO Research Institute

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9856930/9856648/09857080.pdf?arnumber=9857080

Reference50 articles.

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2. Multiple futures prediction;tang;Advances in neural information processing systems,2019

3. Weakly Supervised Action Learning with RNN Based Fine-to-Coarse Modeling

4. Synthetic distracted driving (syndd1) dataset for analyzing distracted behaviors and various gaze zones of a driver;rahman,2022

5. Learning spatiotemporal representation with pseudo-3d residual networks;qiu;Proceedings of the IEEE International Conference on Computer Vision,2017

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