Facial Inpainting
21 papers with code • 3 benchmarks • 4 datasets
Facial inpainting (or face completion) is the task of generating plausible facial structures for missing pixels in a face image.
( Image credit: SymmFCNet )
Libraries
Use these libraries to find Facial Inpainting models and implementationsLatest papers with no code
Face Swap via Diffusion Model
This technical report presents a diffusion model based framework for face swapping between two portrait images.
Learning Position-Aware Implicit Neural Network for Real-World Face Inpainting
Face inpainting requires the model to have a precise global understanding of the facial position structure.
Personalized Face Inpainting with Diffusion Models by Parallel Visual Attention
Specifically, we insert parallel attention matrices to each cross-attention module in the denoising network, which attends to features extracted from reference images by an identity encoder.
DIFAI: Diverse Facial Inpainting using StyleGAN Inversion
Image inpainting is an old problem in computer vision that restores occluded regions and completes damaged images.
Contrastive Learning for Diverse Disentangled Foreground Generation
We introduce a new method for diverse foreground generation with explicit control over various factors.
ShowFace: Coordinated Face Inpainting with Memory-Disentangled Refinement Networks
Furthermore, to better improve the inter-coordination between the corrupted and non-corrupted regions and enhance the intra-coordination in corrupted regions, we design InCo2 Loss, a pair of similarity based losses to constrain the feature consistency.
FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment
Unlike previous work, we offer a subject agnostic swapping scheme that can be applied to pairs of faces without requiring training on those faces.
Contrastive Attention Network with Dense Field Estimation for Face Completion
This multi-scale architecture is beneficial for the decoder to utilize discriminative representations learned from encoders into images.
3DFaceFill: An Analysis-By-Synthesis Approach to Face Completion
Existing face completion solutions are primarily driven by end-to-end models that directly generate 2D completions of 2D masked faces.
Deep Face Video Inpainting via UV Mapping
In Stage I, we perform face inpainting in the UV space.