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DPPnet: Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction

Created by Hyeonwoo Noh, Paul Hongsuck Seo and Bohyung Han at POSTECH cvlab

Project page: [http://cvlab.postech.ac.kr/research/dppnet/]

Introduction

DPPnet is state-of-the-art Image Question Answering algorithm using dynamic parameter prediction to handle various types of questions.

Detailed description of the system will be provided by our technical report arXiv tech report

Citation

If you're using this code in a publication, please cite our papers.

@article{noh2015image,
  title={Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction},
  author={Noh, Hyeonwoo and Seo, Paul Hongsuck and Han, Bohyung},
  journal={arXiv preprint arXiv:1511.05756},
  year={2015}
}

Licence

This software is for research purpose only. Check LICENSE file for details.

System Requirements

Dependencies

Setup

Run "setup.sh" for setting up.

Testing

Scripts for testing is in "006_test_DPPnet". Use following commands for testing. 0. Run ./gen_simulinks.sh 0. Run th vqa_test.lua 0. Results will be saved in "006_test_DPPnet/save_result_vqa_test/results/"

Training

Following steps are required for training. 0. Train DPPnet with fixed cnn feature (004_train_DPPnet_fixed_cnn) 0. Finetune CNN from the model trained in the previous step (005_train_DPPnet_finetune_cnn)

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