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Memes have become an ubiquitous social media entity and the processing andanalysis of suchmultimodal data is currently an active area of research. Thispaper presents our work on theMemotion Analysis shared task of SemEval 2020,which involves the sentiment and humoranalysis of memes. We propose a systemwhich uses different bimodal fusion techniques toleverage the inter-modaldependency for sentiment and humor classification tasks. Out of allourexperiments, the best system improved the baseline with macro F1 scores of0.357 on SentimentClassification (Task A), 0.510 on Humor Classification (TaskB) and 0.312 on Scales of SemanticClasses (Task C).

DSC IIT-ISM at SemEval-2020 Task 8: Bi-Fusion Techniques for Deep Meme Emotion Analysis