Meme Classification

20 papers with code • 2 benchmarks • 4 datasets

Meme classification refers to the task of classifying internet memes.

Libraries

Use these libraries to find Meme Classification models and implementations

Most implemented papers

Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features

gokulkarthik/hateclipper 12 Oct 2022

A simple classifier based on the FIM representation is able to achieve state-of-the-art performance on the Hateful Memes Challenge (HMC) dataset with an AUROC of 85. 8, which even surpasses the human performance of 82. 65.

MemeFier: Dual-stage Modality Fusion for Image Meme Classification

ckoutlis/memefier 6 Apr 2023

Hate speech is a societal problem that has significantly grown through the Internet.

Decoding the Underlying Meaning of Multimodal Hateful Memes

social-ai-studio/hatred 28 May 2023

Recent studies have proposed models that yielded promising performance for the hateful meme classification task.

MemeGraphs: Linking Memes to Knowledge Graphs

vasilikikou/memegraphs 28 May 2023

In this work, we propose to use scene graphs, that express images in terms of objects and their visual relations, and knowledge graphs as structured representations for meme classification with a Transformer-based architecture.

Mapping Memes to Words for Multimodal Hateful Meme Classification

miccunifi/issues 12 Oct 2023

Multimodal image-text memes are prevalent on the internet, serving as a unique form of communication that combines visual and textual elements to convey humor, ideas, or emotions.

BanglaAbuseMeme: A Dataset for Bengali Abusive Meme Classification

hate-alert/banglaabusememe 18 Oct 2023

Finally, we perform a qualitative error analysis of the misclassified memes of the best-performing text-based, image-based and multimodal models.

MATK: The Meme Analytical Tool Kit

social-ai-studio/matk 11 Dec 2023

The rise of social media platforms has brought about a new digital culture called memes.