Methods › Computer Vision › Multi-Modal Methods › EmbraceNet
EmbraceNet: A robust deep learning architecture for multimodal classification
EmbraceNet
Introduced by Jun-Ho Choi et al. in EmbraceNet: A robust deep learning architecture for multimodal classification
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The archive carries no description for this method.
Papers archive 2025-07-28
4 shown of 4, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Using Scene and Semantic Features for Multi-modal Emotion Recognition 1 Aug 2023 · 0 repositories · arXiv:2308.00228
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GLAMI-1M: A Multilingual Image-Text Fashion Dataset 17 Nov 2022 · 1 repository · arXiv:2211.14451
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EmbraceNet for Activity: A Deep Multimodal Fusion Architecture for Activity Recognition 29 Apr 2020 · 0 repositories · arXiv:2004.13918
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EmbraceNet: A robust deep learning architecture for multimodal classification 19 Apr 2019 · 2 repositories · arXiv:1904.09078
Tasks archive 2025-07-28
11 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections