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 131–140 of 381 papers

TitleStatusHype
CG-NeRF: Conditional Generative Neural Radiance Fields—0
EFHQ: Multi-purpose ExtremePose-Face-HQ dataset—0
A Study of the Human Perception of Synthetic Faces—0
Adversarial Identity Injection for Semantic Face Image Synthesis—0
Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously—0
EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model—0
Dynamic Graph Learning With Content-Guided Spatial-Frequency Relation Reasoning for Deepfake Detection—0
A Hybrid Model for Identity Obfuscation by Face Replacement—0
FlowVQTalker: High-Quality Emotional Talking Face Generation through Normalizing Flow and Quantization—0
FTGAN: A Fully-trained Generative Adversarial Networks for Text to Face Generation—0
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