Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models-Reference-Cited by-同舟云学术

Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models

Published:2021 Issue: Volume: Page:459-473
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Daunhawer Imant,Sutter Thomas M.,Marcinkevičs Ričards,Vogt Julia E.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-71278-5_33

Reference42 articles.

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3. Baltrušaitis, T., Ahuja, C., Morency, L.P.: Multimodal machine learning: a survey and taxonomy. IEEE Trans. Pattern Anal. Mach. Intell. 41(2), 423–443 (2019)

4. Bouchacourt, D., Tomioka, R., Nowozin, S.: Multi-level variational autoencoder: learning disentangled representations from grouped observations. In: AAAI Conference on Artificial Intelligence (2018)

5. Chartsias, A., et al.: Disentangled representation learning in cardiac image analysis. Med. Image Anal. 58, 101535 (2019)

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