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CARAT
Cheng Pengが第一著者,Web3系の例のZhejiang University
概要
入力がクロスモーダルな感情認識における研究
SoTAをタッっせいした
Intro
This paper addresses the MMER task that identifies multiple emotions from the multi-modal inputs.
Related works
There are mainly two types of methods
aggregation-based: concatenation
alignment-based: neglect the specificity of each modality
hybrid-method: fusion of the above
Proposed method
By using shuffling among modality dimensions, the proposed method implemented the shuffling among modalities and samples.
Created new co-occurrences among positive samples and negative samples.
Experiment
Preparing a lot of datasets such as BR, LP, MulT
感想
上がった数値は一部であり，非常にインクリメンタルな印象に思えた
手法自体のアイデアは面白いと思った．
Cheng Pengが第一著者,Web3系の例のZhejiang University
概要
入力がクロスモーダルな感情認識における研究
SoTAをタッっせいした
Intro
This paper addresses the MMER task that identifies multiple emotions from the multi-modal inputs.
Related works
There are mainly two types of methods
aggregation-based: concatenation
alignment-based: neglect the specificity of each modality
hybrid-method: fusion of the above
Proposed method
By using shuffling among modality dimensions, the proposed method implemented the shuffling among modalities and samples.
Created new co-occurrences among positive samples and negative samples.
Experiment
Preparing a lot of datasets such as BR, LP, MulT
感想
上がった数値は一部であり，非常にインクリメンタルな印象に思えた
手法自体のアイデアは面白いと思った．