Papers › FaceController: Controllable Attribute Editing for Face in the Wild

FaceController: Controllable Attribute Editing for Face in the Wild

23 Feb 2021arXiv:2102.11464archive 2025-07-28

Zhiliang Xu, Xiyu Yu, Zhibin Hong, Zhen Zhu, Junyu Han, Jingtuo Liu, Errui Ding, Xiang Bai

Face attribute editing aims to generate faces with one or multiple desired face attributes manipulated while other details are preserved. Unlike prior works such as GAN inversion, which has an expensive reverse mapping process, we propose a simple feed-forward network to generate high-fidelity manipulated faces. By simply employing some existing and easy-obtainable prior information, our method can control, transfer, and edit diverse attributes of faces in the wild. The proposed method can consequently be applied to various applications such as face swapping, face relighting, and makeup transfer. In our method, we decouple identity, expression, pose, and illumination using 3D priors; separate texture and colors by using region-wise style codes. All the information is embedded into adversarial learning by our identity-style normalization module. Disentanglement losses are proposed to enhance the generator to extract information independently from each attribute. Comprehensive quantitative and qualitative evaluations have been conducted. In a single framework, our method achieves the best or competitive scores on a variety of face applications.

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Tasks

AttributeDisentanglementFace Swapping

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Face Swapping FaceForensics++ FaceController FID 3.51 #13 of 17 Archive leaderboard report
Face Swapping FaceForensics++ FaceSwap FID 3.81 #14 of 17 Archive leaderboard report
Face Swapping FaceForensics++ FaceShifter FID 4.05 #15 of 17 Archive leaderboard report
Face Swapping FaceForensics++ DeepFake FID 4.29 #16 of 17 Archive leaderboard report
Face Swapping FaceForensics++ FSGAN FID 4.35 #17 of 17 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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