basic_vqa

basic_vqa

Pytorch implementation of the paper - VQA: Visual Question Answering (https://arxiv.org/pdf/1505.00468.pdf).

Usage

1. Clone the repositories.

$ git clone https://github.com/tbmoon/basic_vqa.git

2. Download and Preproccess VQA Datasets

$ cd basic_vqa/utils
$ ./preprocess.sh

3. Train model for VQA task.

$ cd ..
$ python3 train.py

Results

• Comparison Result

Model	Metric	Dataset	Accuracy	Source
Paper Model	Open-Ended	VQA v2	54.08	VQA Challenge
My Model	Multiple Choice	VQA v2	54.72

• Loss and Accuracy on VQA datasets v2

References

• Paper implementation

  • Paper: VQA: Visual Question Answering
  • URL: https://arxiv.org/pdf/1505.00468.pdf

• Pytorch tutorial

  • URL: https://pytorch.org/tutorials/
  • Github: https://github.com/yunjey/pytorch-tutorial
  • Github: https://github.com/GunhoChoi/PyTorch-FastCampus

• Preprocessing

  • Tensorflow implementation of N2NNM
  • Github: https://github.com/ronghanghu/n2nmn