SOTAVerified

Talking Face Generation

Talking face generation aims to synthesize a sequence of face images that correspond to given speech semantics

( Image credit: Talking Face Generation by Adversarially Disentangled Audio-Visual Representation )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 81–90 of 110 papers

TitleStatusHype
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder—0
UniFLG: Unified Facial Landmark Generator from Text or Speech—0
Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation—0
EMMN: Emotional Motion Memory Network for Audio-driven Emotional Talking Face Generation—0
LipFormer: High-Fidelity and Generalizable Talking Face Generation With a Pre-Learned Facial Codebook—0
Emotional Talking Faces: Making Videos More Expressive and Realistic—0
Memories are One-to-Many Mapping Alleviators in Talking Face Generation—0
SyncTalkFace: Talking Face Generation with Precise Lip-Syncing via Audio-Lip Memory—0
Taiwanese-Accented Mandarin and English Multi-Speaker Talking-Face Synthesis System—0
StableFace: Analyzing and Improving Motion Stability for Talking Face Generation—0
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All datasetsCREMA-DLRW

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EmoGenEmoAcc83.2—Unverified
#ModelMetricClaimedVerifiedStatus
1LipGANLMD0.6—Unverified