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LipFormer: High-Fidelity and Generalizable Talking Face Generation With a Pre-Learned Facial Codebook

CVPR 2023 · Image generation › Editing and style transfer · approach: Talking face generation · 35 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use LipFormer with a pre-learned facial codebook and adaptive warping rather than SyncTalkFaceTalking face generation · LRS2PSNR: 32.529 -> 33.497Helped
use LipFormer with a pre-learned facial codebook and adaptive warping rather than SyncTalkFaceTalking face generation · LRS2LMD: 1.387 -> 1.261Helped
use LipFormer rather than Wav2LipTalking face generation · LRS2LSE-D: 5.995 -> 6.408Hurt
use LipFormer rather than Wav2LipTalking face generation · LRS2LSE-C: 8.797 -> 7.874Hurt
use LipFormer rather than Wav2LipTalking face generation · YouTubeHQPSNR: 25.971 -> 33.249Helped
use LipFormer rather than Wav2LipTalking face generation · YouTubeHQLMD: 2.473 -> 1.357Helped
remove Adaptive Face Warping (ablation)LipFormer · YouTubeHQPSNR: 31.980 -> 33.249Hurt
remove Adaptive Face Warping (ablation)LipFormer · YouTubeHQSSIM: 0.845 -> 0.876Hurt
remove FFHQ pre-training (ablation)LipFormer · YouTubeHQPSNR: 31.637 -> 33.249Hurt
remove FFHQ pre-training (ablation)LipFormer · YouTubeHQSSIM: 0.833 -> 0.876Hurt
train the Transformer and decoder separately instead of using Gumbel-softmax for end-to-end training (ablation)LipFormer · LipFormer trainingcross-entropy loss convergenceHurt

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