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Sequential Variational Autoencoder with Adversarial Classifier for Video Disentanglement
In this paper, we propose a sequential variational autoencoder for video disentanglement, which is a representation learning method that can be used to separately extract static and dynamic features from videos. Building sequential variational autoencoders with a two-stream architecture induces indu...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006877/ https://www.ncbi.nlm.nih.gov/pubmed/36904719 http://dx.doi.org/10.3390/s23052515 |