TIB-VA at SemEval-2022 Task 5: A Multimodal Architecture for the Detection and Classification of Misogynous Memes
SemEval-2022 Task 5: MAMI - Multimedia Automatic Misogyny Identification, co-located with NAACL 2022
Python (3.7) libraries: clip, torch, numpy, sklearn - "requirements.txt"
The model architecture code is in the file "train_multitask.py"
We provided the model outputs for Task A & B under the directory "mami_submissions". It includes the best submissions for each task ("answer.txt").
The dataset files are under "data". Images need to be downloaded and put under the parent folder "data" as "training_images" and "test_images". Download link.
Please cite if you find the resource useful:
@inproceedings{DBLP:conf/semeval/HakimovCE22,
author = {Sherzod Hakimov and
Gullal Singh Cheema and
Ralph Ewerth},
editor = {Guy Emerson and
Natalie Schluter and
Gabriel Stanovsky and
Ritesh Kumar and
Alexis Palmer and
Nathan Schneider and
Siddharth Singh and
Shyam Ratan},
title = {{TIB-VA} at SemEval-2022 Task 5: {A} Multimodal Architecture for the
Detection and Classification of Misogynous Memes},
booktitle = {Proceedings of the 16th International Workshop on Semantic Evaluation,
SemEval@NAACL 2022, Seattle, Washington, United States, July 14-15,
2022},
pages = {756--760},
publisher = {Association for Computational Linguistics},
year = {2022},
url = {https://doi.org/10.18653/v1/2022.semeval-1.105},
doi = {10.18653/v1/2022.semeval-1.105},
timestamp = {Mon, 01 Aug 2022 17:09:21 +0200},
biburl = {https://dblp.org/rec/conf/semeval/HakimovCE22.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}