PUC Chile team at VQA-Med 2021: approaching VQA as a classification task via fine-tuning a pretrained CNN

Ricardo Schilling, Pablo Messina, Denis Parra, Hans Löbel
2021 Conference and Labs of the Evaluation Forum  
This paper describes the submission of the IALab group of the Pontifical Catholic University of Chile to the Medical Domain Visual Question Answering (VQA-Med) task. Our participation was rather simple: we approached the problem as image classification. We took a DenseNet121 with its weights pre-trained in ImageNet and fine-tuned it with the VQA-Med 2020 dataset labels to predict the answer. Different answers were treated as different classes, and the questions were disregarded for simplicity
more » ... nce essentially they all ask for abnormalities. With this very simple approach we ranked 7th among 11 teams, with a test set accuracy of 0.236.
dblp:conf/clef/SchillingMPL21 fatcat:tdgeipsh7jh2ximy63r4uksbna