finetune训练效果不好，麻烦看看 #22
Description
训练前效果：
训练后效果：
相关配置：
experiment: 'portrait4d-v2-vfhq512-toy'
cfg: 'vfhq'
outdir: './training-runs-portrait4d-v2'
data: './data/VFHQ_sub50_512_416/'
gpus: 1
batch: 2
#gpus: 4
#batch: 8
#kimg: 18000
kimg: 12000
g_module: 'training.reconstructor.triplane_reconstruct.TriPlaneReconstructorNeutralize'
d_module: 'training.discriminator.dual_discriminator.DualDiscriminatorDeform'
glr: 1e-4
dlr: 1e-4
g_has_superresolution: True
g_has_background: True
g_flame_full: True
g_num_blocks_neutral: 4
g_num_blocks_motion: 4
g_motion_map_layers: 2
d_has_superresolution: True
d_has_uv: True
d_has_seg: True
patch_scale: 1.0
use_ws_ones: False # If true, ws==one for superresolution
use_flame_mot: False # If true, use flame parameters as motion embedding
cross_lr_scale: 2.5 # Learning rate scaling factor for motion-related layers
static: False # If true, disable all motion-control and learn static 3d reconstruction model instead
resume: './pretrained_models/portrait4d-static-genhead512.pkl' # Resume from pre-trained static model
resume_kimg: 10000
resume_fix: './pretrained_models/portrait4d-static-genhead512.pkl' # Checkpoint of pre-trained static model for multi-view data synthesis
snap: 10
density_reg_every: 4
density_reg: 1
reg_type: 'G_fix_img'
mot_aug_prob: 0.9 # Probability of using arbitrary-view driving image for motion embedding extraction
g_fix_reg_img_aug: True # Rescale the synthesized heads of static model to compensate for the scale inconsistency issue between heads with and without eye blink
neural_rendering_resolution_initial: 128
max_num: -1 # 'Max number of videos used for training', metavar='INT', type=click.IntRange(min=-1), default=-1, required=False, show_default=True