Facial Editing

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

12 shown of 12 papers with code (29 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Pivotal Tuning for Latent-based Editing of Real Images
  10 Jun 2021 3 repositories listed Syntology ran 2 of 4 samples · 2 unverified
  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.
• E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversion
  23 Oct 2023 2 repositories listed
  Based on this disentanglement, face swapping can be simplified as style and mask swapping.
• Neural Face Editing with Intrinsic Image Disentangling
  13 Apr 2017 2 repositories listed
  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.
• SEED: A Benchmark Dataset for Sequential Facial Attribute Editing with Diffusion Models
  31 May 2025 1 repository listed
  However, sequential editing introduces significant challenges in edit attribution and detection robustness, further complicated by the lack of large-scale, finely annotated benchmarks tailored explicitly for this task.
• A Generalist FaceX via Learning Unified Facial Representation
  31 Dec 2023 1 repository listed
  This work presents FaceX framework, a novel facial generalist model capable of handling diverse facial tasks simultaneously.
• Robust Sequential DeepFake Detection
  26 Sep 2023 1 repository listed
  However, existing methods only focus on detecting one-step facial manipulation.
• Detecting and Recovering Sequential DeepFake Manipulation
  5 Jul 2022 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Moreover, we build a comprehensive benchmark and set up rigorous evaluation protocols and metrics for this new research problem.
• TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing
  31 Mar 2022 1 repository listed Syntology ran 6 of 15 samples · 9 unverified
  In this study, we highlight the importance of interaction in a dual-space GAN for more controllable editing.
• StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN
  8 Mar 2022 1 repository listed Syntology ran 1 of 8 samples · 7 unverified
  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.
• Stitch it in Time: GAN-Based Facial Editing of Real Videos
  20 Jan 2022 1 repository listed Syntology ran 2 of 5 samples · 3 unverified
  The ability of Generative Adversarial Networks to encode rich semantics within their latent space has been widely adopted for facial image editing.
• SemanticStyleGAN: Learning Compositional Generative Priors for Controllable Image Synthesis and Editing
  4 Dec 2021 1 repository listed
  When combined with editing methods designed for StyleGANs, it can achieve a more fine-grained control to edit synthesized or real images.
• Talk-to-Edit: Fine-Grained Facial Editing via Dialog
  9 Sep 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  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.

Syntology lines on 6 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.