Few-Shot Adversarial Learning of Realistic Neural Talking Head Models

ICCV 2019 Egor ZakharovAliaksandra ShysheyaEgor BurkovVictor Lempitsky

Several recent works have shown how highly realistic human head images can be obtained by training convolutional neural networks to generate them. In order to create a personalized talking head model, these works require training on a large dataset of images of a single person... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Talking Head Generation VoxCeleb1 - 1-shot learning Few-shot Adversarial Model FID 43.0 # 1
Talking Head Generation VoxCeleb1 - 32-shot learning Few-shot Adversarial Model FID 29.5 # 1
Talking Head Generation VoxCeleb1 - 8-shot learning Few-shot Adversarial Model FID 38.0 # 1
Talking Head Generation VoxCeleb2 - 1-shot learning Few-shot Adversarial Model FID 48.5 # 2
Talking Head Generation VoxCeleb2 - 32-shot learning Few-shot Adversarial Model FID 30.6 # 1
Talking Head Generation VoxCeleb2 - 8-shot learning Few-shot Adversarial Model FID 42.2 # 2

Methods used in the Paper


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