Papers with Code 아카이브
Face Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 평가표
- 0
- 보존된 평가 기록
- 0
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.
<span style="color:grey; opacity: 0.6">( Image credit: Progressive Growing of GANs for Improved Quality, Stability, and Variation )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
F-Bench: Rethinking Human Preference Evaluation Metrics for Benchmarking Face Generation, Customization, and Restoration
StyleDiT: A Unified Framework for Diverse Child and Partner Faces Synthesis with Style Latent Diffusion Transformer
VQTalker: Towards Multilingual Talking Avatars through Facial Motion Tokenization
GoHD: Gaze-oriented and Highly Disentangled Portrait Animation with Rhythmic Poses and Realistic Expression
BENet: A Cross-domain Robust Network for Detecting Face Forgeries via Bias Expansion and Latent-space Attention
PortraitTalk: Towards Customizable One-Shot Audio-to-Talking Face Generation
VariFace: Fair and Diverse Synthetic Dataset Generation for Face Recognition
IF-MDM: Implicit Face Motion Diffusion Model for High-Fidelity Realtime Talking Head Generation
Fairer Analysis and Demographically Balanced Face Generation for Fairer Face Verification
Sonic: Shifting Focus to Global Audio Perception in Portrait Animation
ConsistentAvatar: Learning to Diffuse Fully Consistent Talking Head Avatar with Temporal Guidance
EmotiveTalk: Expressive Talking Head Generation through Audio Information Decoupling and Emotional Video Diffusion
Comparative Analysis of Audio Feature Extraction for Real-Time Talking Portrait Synthesis
Analyzing and Improving the Skin Tone Consistency and Bias in Implicit 3D Relightable Face Generators
LES-Talker: Fine-Grained Emotion Editing for Talking Head Generation in Linear Emotion Space
DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking Head Video Generation
Beyond Fixed Topologies: Unregistered Training and Comprehensive Evaluation Metrics for 3D Talking Heads
MimicTalk: Mimicking a personalized and expressive 3D talking face in minutes
EmoGene: Audio-Driven Emotional 3D Talking-Head Generation
Emo3D: Metric and Benchmarking Dataset for 3D Facial Expression Generation from Emotion Description
LaDTalk: Latent Denoising for Synthesizing Talking Head Videos with High Frequency Details
Learning Frame-Wise Emotion Intensity for Audio-Driven Talking-Head Generation
CemiFace: Center-based Semi-hard Synthetic Face Generation for Face Recognition
Face Forgery Detection with Elaborate Backbone
Single Image, Any Face: Generalisable 3D Face Generation
JEAN: Joint Expression and Audio-guided NeRF-based Talking Face Generation
MM2Latent: Text-to-facial image generation and editing in GANs with multimodal assistance
DreamHead: Learning Spatial-Temporal Correspondence via Hierarchical Diffusion for Audio-driven Talking Head Synthesis
MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detection
StyleTalk++: A Unified Framework for Controlling the Speaking Styles of Talking Heads
EMOdiffhead: Continuously Emotional Control in Talking Head Generation via Diffusion
DiffTED: One-shot Audio-driven TED Talk Video Generation with Diffusion-based Co-speech Gestures
KAN-Based Fusion of Dual-Domain for Audio-Driven Facial Landmarks Generation
SVP: Style-Enhanced Vivid Portrait Talking Head Diffusion Model
A Key-Driven Framework for Identity-Preserving Face Anonymization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.