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[ECCV 2020] In-Domain GAN Inversion for Real Image Editing

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Following is the training log. ``` dnnlib: Running training.training_loop.training_loop() on localhost... GPU available: True GPU devices: /device:GPU:0 >>>>> Create Session Dataset directory: . Streaming data using training.dataset.TFRecordDataset... tfrecord_dir: .\custom-images Dataset...

I was wondering if it is possible to use the semantic diffusions in other domains that does not include a human face. In the colab provided there is a face...

I've tried several different versions of tensorflow, but all of them reported errors which seems related to environment when I tried to run train_encoder.py. I would appreciate it very much...

I edit real faces, all the aged faces with eyeglasses, it is strange. Should the face attributes be disentangled? Anyone encounter this question? Any solutions?

Thank you for your great work!! That'cool!! I would like to ask, do you mean to train the Encoder with the FFHQ dataset, and then use 7000 real face images...

Does someone has a Stylegan2 implementation? Thank you

When i am trying to training the encoder, I got the error as below: tensorflow.python.framework.errors_impl.FailedPreconditionError: datasets/custom-dataset; Is a directory [[{{node IteratorGetNext}}]]