MDN-VQG

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## MDN-VQG : Multimodal Differential Network for Visual Question Generation

-- [[Project Page](https://badripatro.github.io/MDN-VQG/)]

-- [[Paper: EMNLP-2018](http://aclweb.org/anthology/D18-1434)]

-- [[Pseudo Code: EMNLP-2018 Paper](https://github.com/badripatro/Visual_Question_Generation)]

## Introduction

## Main

Torch implementation of an "Multimodal Differential Network for Visual Question Generation" .
### Training Step:

1. Download VQG dataset from MicrosoftVQG site.
    2. Create train,val and test json file.
    3. Preprocess the MSCOCO image file using prepro/prepro_img.lua for joint model and prepro/prepro_img_att.lua for attention model.
    4. Find the exemplar(Supporting and oppsing) Image using /data/knn_image.m
    5. Run : th training.lua

### Reference

```
@InProceedings{D18-1434,
  author = 	"Patro, Badri Narayana
		and Kumar, Sandeep
		and Kurmi, Vinod Kumar
		and Namboodiri, Vinay",
  title = 	"Multimodal Differential Network for Visual Question Generation",
  booktitle = 	"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
  year = 	"2018",
  publisher = 	"Association for Computational Linguistics",
  pages = 	"4002--4012",
  location = 	"Brussels, Belgium",
  url = 	"http://aclweb.org/anthology/D18-1434"
}
```

MDN-VQG

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