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This paper describes our contribution to SemEval 2020 Task 8: MemotionAnalysis. Our system learns multi-modal embeddings from text and images inorder to classify Internet memes by sentiment. Our model learns text embeddingsusing BERT and extracts features from images with DenseNet, subsequentlycombining both features through concatenation. We also compare our results withthose produced by DenseNet, ResNet, BERT, and BERT-ResNet. Our results showthat image classification models have the potential to help classifying memes,with DenseNet outperforming ResNet. Adding text features is however not alwayshelpful for Memotion Analysis.

NUAA-QMUL at SemEval-2020 Task 8: Utilizing BERT and DenseNet for Internet Meme Emotion Analysis