An official PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language", NeurIPS 2018
A PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language". This code implements a Text-Adaptive Generative Adversarial Network (TAGAN) for manipulating images with natural language.
Download a pretrained English word vectors. You can see the list of pretrained vectors on this page.
The caption data is from this repository. After downloading, modify CONFIG
file so that all paths of the datasets point to the data you downloaded.
Please put these files in ./models/
folder.
scripts/preprocess_caption.sh
scripts/train_[flowers/birds].sh
train.py
.scripts/test_[flowers/birds].sh
./test/result_[flowers/birds]/index.html
.Please cite our paper when you use this code.
@inproceedings{nam2018tagan,
title={Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language},
author={Nam, Seonghyeon and Kim, Yunji and Kim, Seon Joo},
booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
year={2018}
}
Please contact [email protected] if you have any question about this work.