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LGVTON: A Landmark Guided Approach for Model to Person Virtual Try-On

This repository contains the Keras implementation of LGVTON (accepted for publication in Multimedia Tools and Applications journal)

This is an inference code. The checkpoints and a sample dataset with some annotated sample fashion landmarks on the MPV dataset is upload at,

https://drive.google.com/drive/folders/1v8ORGRVbTVsE9Mcw6JVxpintEfKLH3HR?usp=sharing

Test code: bash run.sh

The code is tested in the following versions: keras = '2.2.4' tensorflow = '1.14.0' python = '3.5'

In case you use this code please consider citing

  @article{roy2020lgvton,
    title={Lgvton: A landmark guided approach to virtual try-on},
    author={Roy, Debapriya and Santra, Sanchayan and Chanda, Bhabatosh},
    journal={arXiv preprint arXiv:2004.00562},
    year={2020}
  }