M-SENA: An Integrated Platform for Multimodal Sentiment Analysis

Huisheng Mao, Ziqi Yuan, Hua Xu, Wenmeng Yu, Yihe Liu +1 more
3/23/2022
cs.AIcs.MM

Official code: thuiar/M-SENA (105 stars, GPL-3.0, last commit 2022-03-30). 2 more implementations below.

Abstract

M-SENA is an open-sourced platform for Multimodal Sentiment Analysis. It aims to facilitate advanced research by providing flexible toolkits, reliable benchmarks, and intuitive demonstrations. The platform features a fully modular video sentiment analysis framework consisting of data management, feature extraction, model training, and result analysis modules. In this paper, we first illustrate the overall architecture of the M-SENA platform and then introduce features of the core modules. Reliable baseline results of different modality features and MSA benchmarks are also reported. Moreover, we use model evaluation and analysis tools provided by M-SENA to present intermediate representation visualization, on-the-fly instance test, and generalization ability test results. The source code of the platform is publicly available at https://github.com/thuiar/M-SENA.

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Code Implementations(3)

thuiar/M-SENAOfficial100%
GPL-3.0

M-SENA: All-in-One Platform for Multimodal Sentiment Analysis

1056Jan 11, 20214 years agoGPL-3.0
thuiar/MMSACommunity100%
MIT

MMSA is a unified framework for Multimodal Sentiment Analysis.

1,045137PythonApr 21, 20201 years agoMIT
datasetframeworkmulti-task-learningmultimodal-sentiment-analysis
thuiar/MMSA-FETCommunity100%
GPL-3.0

A Tool for extracting multimodal features from videos.

23027PythonNov 22, 20213 years agoGPL-3.0
multimodal-deep-learningmultimodal-sentiment-analysis

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Cite this paper

@article{mao2022msena,
  title  = {M-SENA: An Integrated Platform for Multimodal Sentiment Analysis},
  author = {Huisheng Mao and Ziqi Yuan and Hua Xu and Wenmeng Yu and Yihe Liu and Kai Gao},
  year   = {2022},
  eprint = {2203.12441},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2203.12441}
}

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