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Pytorch implementation of paper "One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing"

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One-Shot Free-View Neural Talking Head Synthesis

Unofficial pytorch implementation of paper "One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing"

We train and test it only on python 3.6 and pytorch 1.7.0.

Driving | FOMM | Ours:
show

Free-View:
show

Train:

python run.py --config config/vox-256.yaml --device_ids 0,1,2,3,4,5,6,7

Demo:

python demo.py --config config/vox-256.yaml --checkpoint path/to/checkpoint --source_image path/to/source --driving_video path/to/driving --relative --adapt_scale --find_best_frame

free-view (e.g. yaw=20, pitch=roll=0):

python demo.py --config config/vox-256.yaml --checkpoint path/to/checkpoint --source_image path/to/source --driving_video path/to/driving --relative --adapt_scale --find_best_frame --free_view --yaw 20 --pitch 0 --row 0

Note: run crop-video.py --inp driving_video.mp4 to get crop suggestions and crop the driving video as prompted.

Pretrained Model:

Model Train Set Baidu Netdisk Google Drive
Vox-256-Beta VoxCeleb-v1 Baidu (PW: c0tc) soon
Vox-256-Stable VoxCeleb-v1 soon soon
Vox-256 VoxCeleb-v2 soon soon
Vox-512 VoxCeleb-v2 soon soon

Note: It is recommended that Yaw, Pitch and Roll are within ±45°, ±20° and ±20° respectively for free-view synthesis.

Acknowlegement:

Thanks to NV, AliaksandrSiarohin and DeepHeadPose

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