Facial Editing
11 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Facial Editing
Most implemented papers
Pivotal Tuning for Latent-based Editing of Real Images
The key idea is pivotal tuning - a brief training process that preserves the editing quality of an in-domain latent region, while changing its portrayed identity and appearance.
Neural Face Editing with Intrinsic Image Disentangling
Traditional face editing methods often require a number of sophisticated and task specific algorithms to be applied one after the other --- a process that is tedious, fragile, and computationally intensive.
E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversion
Based on this disentanglement, face swapping can be simplified as style and mask swapping.
Talk-to-Edit: Fine-Grained Facial Editing via Dialog
In this work, we propose Talk-to-Edit, an interactive facial editing framework that performs fine-grained attribute manipulation through dialog between the user and the system.
SemanticStyleGAN: Learning Compositional Generative Priors for Controllable Image Synthesis and Editing
When combined with editing methods designed for StyleGANs, it can achieve a more fine-grained control to edit synthesized or real images.
Stitch it in Time: GAN-Based Facial Editing of Real Videos
The ability of Generative Adversarial Networks to encode rich semantics within their latent space has been widely adopted for facial image editing.
StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN
Our framework elevates the resolution of the synthesized talking face to 1024*1024 for the first time, even though the training dataset has a lower resolution.
TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing
In this study, we highlight the importance of interaction in a dual-space GAN for more controllable editing.
Detecting and Recovering Sequential DeepFake Manipulation
Moreover, we build a comprehensive benchmark and set up rigorous evaluation protocols and metrics for this new research problem.
Robust Sequential DeepFake Detection
However, existing methods only focus on detecting one-step facial manipulation.