Hey all,
For this fake, first I trained Liv's face-set to itself for about 100k. I believe it converged faster and learned more details this way. After that I continued regular training.
For convert options, I used overlay, erode 10, blur 10, rct as color transfer and enabled super resolution. You can find model details below.
Enjoy.
https://mrdeepfakes.com/video/3128/liv-tyler-had-it-rough
Mega:
https://mega.nz/#!GyRiQAhT!wh3K3RwdJLEpR_5svqNXl11L5JSIfNEg01cg7Wq3Jbo
===== Model summary =====
== Model name: SAE
==
== Current iteration: 154872
==
== Model options:
== |== batch_size : 8
== |== sort_by_yaw : False
== |== random_flip : False
== |== resolution : 144
== |== face_type : f
== |== learn_mask : True
== |== optimizer_mode : 2
== |== archi : df
== |== ae_dims : 512
== |== e_ch_dims : 42
== |== d_ch_dims : 21
== |== remove_gray_border : False
== |== multiscale_decoder : False
== |== pixel_loss : False
== |== face_style_power : 10.0
== |== bg_style_power : 10.0
For this fake, first I trained Liv's face-set to itself for about 100k. I believe it converged faster and learned more details this way. After that I continued regular training.
For convert options, I used overlay, erode 10, blur 10, rct as color transfer and enabled super resolution. You can find model details below.
Enjoy.
https://mrdeepfakes.com/video/3128/liv-tyler-had-it-rough
Mega:
https://mega.nz/#!GyRiQAhT!wh3K3RwdJLEpR_5svqNXl11L5JSIfNEg01cg7Wq3Jbo
===== Model summary =====
== Model name: SAE
==
== Current iteration: 154872
==
== Model options:
== |== batch_size : 8
== |== sort_by_yaw : False
== |== random_flip : False
== |== resolution : 144
== |== face_type : f
== |== learn_mask : True
== |== optimizer_mode : 2
== |== archi : df
== |== ae_dims : 512
== |== e_ch_dims : 42
== |== d_ch_dims : 21
== |== remove_gray_border : False
== |== multiscale_decoder : False
== |== pixel_loss : False
== |== face_style_power : 10.0
== |== bg_style_power : 10.0