I believe he means with the current model, in which case not much can be done. you can play with the masking and the swapped img a bit if youre familiar with opencv.
I believe he means with the current model, in which case not much can be done. you can play with the masking and the swapped img a bit if youre familiar with opencv.
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see line 218 in train.py
you can control id-loss using opt.lambda_id
I believe he means with the current model, in which case not much can be done. you can play with the masking and the swapped img a bit if youre familiar with opencv.