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Facial Inpainting

Facial inpainting (or face completion) is the task of generating plausible facial structures for missing pixels in a face image.

( Image credit: SymmFCNet )

Papers

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Showing 1–25 of 60 papers

TitleStatusHype
Binary Diffusion Probabilistic Model—0
Look Through Masks: Towards Masked Face Recognition with De-Occlusion Distillation—0
Face Mask Removal with Region-attentive Face InpaintingCode0
Masked Face Recognition with Generative-to-Discriminative Representations—0
ABANet: Attention boundary-aware network for image segmentationCode1
E2F-Net: Eyes-to-Face Inpainting via StyleGAN Latent SpaceCode0
Face Swap via Diffusion ModelCode2
Learning Position-Aware Implicit Neural Network for Real-World Face Inpainting—0
Compensation Sampling for Improved Convergence in Diffusion ModelsCode0
Personalized Face Inpainting with Diffusion Models by Parallel Visual Attention—0
E4S: Fine-grained Face Swapping via Editing With Regional GAN InversionCode1
PATMAT: Person Aware Tuning of Mask-Aware Transformer for Face InpaintingCode1
Reference-Guided Large-Scale Face Inpainting with Identity and Texture ControlCode1
DIFAI: Diverse Facial Inpainting using StyleGAN Inversion—0
Reference Guided Image Inpainting using Facial AttributesCode1
SFI-Swin: Symmetric Face Inpainting with Swin Transformer by Distinctly Learning Face Components DistributionsCode1
Conffusion: Confidence Intervals for Diffusion ModelsCode1
Contrastive Learning for Diverse Disentangled Foreground Generation—0
Masked Face Inpainting Through Residual Attention UNetCode1
HiMFR: A Hybrid Masked Face Recognition Through Face InpaintingCode0
ShowFace: Coordinated Face Inpainting with Memory-Disentangled Refinement Networks—0
Improved Semantic Inpainting Architecture Augmented with a Facial Landmark Detector—0
FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment—0
Non-Deterministic Face Mask Removal Based On 3D PriorsCode1
Do Inpainting Yourself: Generative Facial Inpainting Guided by ExemplarsCode1
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