@inproceedings{10.1145/3430984.3431057,
author = {Jain, Harshil and Patil, Rohit and Jethva, Utsav and Kaoshik, Ronak and Agarawal, Shaurya and Dutta, Ritik and Batra, Nipun},
title = {Generative Fashion for Indian Clothing},
year = {2021},
isbn = {9781450388177},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3430984.3431057},
doi = {10.1145/3430984.3431057},
abstract = {Deep learning-based innovations, particularly GANs, have recently shown great success in fashion modelling for various use cases such as pose and face generation. A famous work, FashionGAN[1], can generate images with modified clothing as per natural language description and uses the DeepFashion dataset, which primarily contains clothing styles of the Western countries. Currently, no dataset caters to Indian style and clothing. Hence, we present a dataset of 12k images and descriptions pertaining to the Indian culture as well as a baseline approach with this work. Deep learning-based innovations in the Indian Fashion context are a relatively new area of research, and we hope our work will be a starting point for other researchers. Code and Dataset: https://github.com/ronakkaoshik42/Generative_fashion},
booktitle = {8th ACM IKDD CODS and 26th COMAD},
pages = {415},
numpages = {1},
location = {Bangalore, India},
series = {CODS COMAD 2021}
}