Integrating Dual-Stream Cross Fusion and Ambiguous Exclude Contrastive Learning for Enhanced Human Action Recognition

Author:

Huang Biaozhang1ORCID,Li Xinde1ORCID

Affiliation:

1. Southeast University, China and Nanjing Center for Applied Mathematics, China

Funder

Key Projects of Key R&D Program of Jiangsu Province

National Natural Science Foundation of China

Shenzhen Science and Technology Program

Publisher

ACM

Reference40 articles.

1. Efficient Hybrid Algorithm for Human Action Recognition

2. Using Discrete Cosine Transform Based Features for Human Action Recognition

3. David Berthelot, Nicholas Carlini, Ekin D Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, and Colin Raffel. 2019. Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring. arXiv preprint arXiv:1911.09785 (2019).

4. Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin. 2020. Unsupervised learning of visual features by contrasting cluster assignments. Advances in neural information processing systems 33 (2020), 9912–9924.

5. An integrated mixed reality system for safety-aware human-robot collaboration using deep learning and digital twin generation

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