Rich Action-Semantic Consistent Knowledge for Early Action Prediction
Author:
Affiliation:
1. School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Haidian, China
2. Department of Computer Science and Technology, Tsinghua University, Beijing, China
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Beijing University of Posts and Telecommunications Excellent Ph.D. Students Foundation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Graphics and Computer-Aided Design,Software
Link
http://xplorestaging.ieee.org/ielx7/83/10346232/10375880.pdf?arnumber=10375880
Reference76 articles.
1. Review of video predictive understanding: Early action recognition and future action prediction;Zhao;arXiv:2107.05140,2021
2. Spherical Panorama Image Watermarking Using Viewpoint Detection
3. Discriminative Multi-instance Multitask Learning for 3D Action Recognition
4. Latent Max-Margin Multitask Learning With Skelets for 3-D Action Recognition
5. Progressive Teacher-Student Learning for Early Action Prediction
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. TODO-Net: Temporally Observed Domain Contrastive Network for 3-D Early Action Prediction;IEEE Transactions on Neural Networks and Learning Systems;2024
2. Adversarial Attention Networks for Early Action Recognition;IEEE Transactions on Emerging Topics in Computational Intelligence;2024
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