NUAA-QMUL-AIIT at Memotion 3: Multi-modal Fusion with Squeeze-and-Excitation for Internet Meme Emotion Analysis
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Abstract (arXiv)
This paper describes the participation of our NUAA-QMUL-AIIT team in the Memotion 3 shared task on meme emotion analysis. We propose a novel multi-modal fusion method, Squeeze-and-Excitation Fusion (SEFusion), and embed it into our system for emotion classification in memes. SEFusion is a simple fusion method that employs fully connected layers, reshaping, and matrix multiplication. SEFusion learns a weight for each modality and then applies it to its own modality feature. We evaluate the performance of our system on the three Memotion 3 sub-tasks. Among all participating systems in this Memotion 3 shared task, our system ranked first on task A, fifth on task B, and second on task C. Our proposed SEFusion provides the flexibility to fuse any features from different modalities. The source code for our method is published on https://github.com/xxxxxxxxy/memotion3-SEFusion.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 10 of its 23 references that are in the map. First posted on arXiv 16 Feb 2023.
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10 of 23 references.
References · 10
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- 2020SemEval-2020 Task 8: Memotion Analysis -- The Visuo-Lingual Metaphor!cited by 77
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- 2019Hate Speech in Pixels: Detection of Offensive Memes towards Automatic Moderationcited by 29
- 2020Attention-based Multi-modal Fusion Network for Semantic Scene Completioncited by 28
- 2020NUAA-QMUL at SemEval-2020 Task 8: Utilizing BERT and DenseNet for Internet Meme Emotion Analysiscited by 4
- 2022Multimodal Feature Extraction for Memes Sentiment Classificationcited by 3
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.