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 61–70 of 110 papers

TitleStatusHype
CP-EB: Talking Face Generation with Controllable Pose and Eye Blinking Embedding—0
CPNet: Exploiting CLIP-based Attention Condenser and Probability Map Guidance for High-fidelity Talking Face Generation—0
Cut Inner Layers: A Structured Pruning Strategy for Efficient U-Net GANs—0
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder—0
Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation—0
DisentTalk: Cross-lingual Talking Face Generation via Semantic Disentangled Diffusion Model—0
DREAM-Talk: Diffusion-based Realistic Emotional Audio-driven Method for Single Image Talking Face Generation—0
EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model—0
EMMN: Emotional Motion Memory Network for Audio-driven Emotional Talking Face Generation—0
EmoSpeaker: One-shot Fine-grained Emotion-Controlled Talking Face Generation—0
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All datasetsCREMA-DLRW

Benchmark Results

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