SOTAVerified

Face Generation

Face generation is the task of generating (or interpolating) new faces from an existing dataset.

The state-of-the-art results for this task are located in the Image Generation parent.

( Image credit: Progressive Growing of GANs for Improved Quality, Stability, and Variation )

Papers

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Showing 201–225 of 381 papers

TitleStatusHype
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder—0
Data Synthesis with Diverse Styles for Face Recognition via 3DMM-Guided Diffusion—0
DeepFace: Face Generation using Deep Learning—0
Dense-Face: Personalized Face Generation Model via Dense Annotation Prediction—0
Detecting Face Synthesis Using a Concealed Fusion Model—0
Differential Generative Adversarial Networks: Synthesizing Non-linear Facial Variations with Limited Number of Training Data—0
DiffTalker: Co-driven audio-image diffusion for talking faces via intermediate landmarks—0
Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation—0
DiffUMI: Training-Free Universal Model Inversion via Unconditional Diffusion for Face Recognition—0
Disentangled Lifespan Face Synthesis—0
DisentTalk: Cross-lingual Talking Face Generation via Semantic Disentangled Diffusion Model—0
Domain Private and Agnostic Feature for Modality Adaptive Face Recognition—0
DreamSalon: A Staged Diffusion Framework for Preserving Identity-Context in Editable Face Generation—0
DREAM-Talk: Diffusion-based Realistic Emotional Audio-driven Method for Single Image Talking Face Generation—0
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis—0
Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning—0
Dynamic Conditional Networks for Few-Shot Learning—0
Dynamic Graph Learning With Content-Guided Spatial-Frequency Relation Reasoning for Deepfake Detection—0
EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model—0
Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously—0
EFHQ: Multi-purpose ExtremePose-Face-HQ dataset—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
EmoTalker: Emotionally Editable Talking Face Generation via Diffusion Model—0
Emotional Conversation: Empowering Talking Faces with Cohesive Expression, Gaze and Pose Generation—0
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