Awesome
Adma-GAN: Attribute-Driven Memory Augmented GANs for Text-to-Image Generation (ACMMM 2022)
Official Pytorch implementation for our paper [arxiv]
Pipeline
Experimental Results on CUB-200-2011 and COCO2014
Dataset
- Download the preprocessed CUB-200-2011 dataset. (including the extracted attribute information)
- Add it to data/CUB-200-2011
- Copy attribute/attributes_captions_embedding.pickle to data/CUB_200_2011/caption/
Training
cd Adma-GAN/code/
python train.py --config=cfg/bird.yml
Citing
If you find Adma-GAN useful in your research, please consider citing our paper:
@inproceedings{wu2022adma,
title={Adma-GAN: Attribute-Driven Memory Augmented GANs for Text-to-Image Generation.},
author={Wu, Xintian and Zhao, Hanbin and Zheng, Liangli and Ding, Shouhong and Li, Xi},
booktitle={Proceedings of the 30th ACM International Conference on Multimedia},
pages={1593--1602},
year={2022}
}