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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 1–10 of 381 papers

TitleStatusHype
Non-Adaptive Adversarial Face Generation—0
Guard Me If You Know Me: Protecting Specific Face-Identity from Deepfakes—0
FaceCrafter: Identity-Conditional Diffusion with Disentangled Control over Facial Pose, Expression, and Emotion—0
FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live ImagesCode1
Robustness in AI-Generated Detection: Enhancing Resistance to Adversarial Attacks—0
MagicPortrait: Temporally Consistent Face Reenactment with 3D Geometric GuidanceCode0
LMME3DHF: Benchmarking and Evaluating Multimodal 3D Human Face Generation with LMMs—0
DiffUMI: Training-Free Universal Model Inversion via Unconditional Diffusion for Face Recognition—0
ID-Booth: Identity-consistent Face Generation with Diffusion ModelsCode1
Data Synthesis with Diverse Styles for Face Recognition via 3DMM-Guided Diffusion—0
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