[WIP] The code for CVPR 2021 paper 'Disentangled Cycle Consistency for Highly-realistic Virtual Try-On' 
python 3.6
pytorch 1.0.0
torchvision 0.3.0
cuda 10.0
opencv
1.VITON
2.VITON-HQ (collected by ourself)
WIP
Hello, Thank you for your great work Can you provide the Pretrained model for this amazing implementation, it will be easy for everyone to test, and it will be much appreciated
Hi, Thansk for your great work and great results! Just can't wait to try it!
Since you mentioned the VITON-HD dataset in the paper, I would like to ask how you obtained it? Was it by direct scaling 2x or some Super Resolution methods used? And will that dataset be public accessible?
start.sh requires disunified_net.py, but this file is not located in the repository. Please provide this file and any other required files. Thank you in advance.
Hello, thank you very much for your work. Can you provide the trial results generated after the test of the VITON dataset, including paired and unmatched？Thank you. The densepose file generated by me is different from yours. Can you provide your own model for using densepose？ @ChongjianGE
Hi, Thanks for your work. When I use the viton to test the model, I realize that label data is missing. So I wanna know how to make a label data of viton? Thanks
I am pleased with your work; the level of completeness is really professional! Do you guys have any plan to release the code for Google Colab? Unfortunately, I can't run the code on my local machine due to some poor factors.
Hello i read the research paper of DCTON
and i confuse in some part like in MPN network we genrate ( M1_cloth and M1_skin ) that means we genrate mask of input image cloth but the image of DCTON netwrok show M1_cloth as output Cloth Mask
if anyone clear this doubt will help me alot.
and also can anyone explain why We send C2 ( targeted Cloth ) in MPN we just generate C1_mask from D ( human Representation ) so why we send C2 In MPN Network
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