Region-Aware Face Swapping
Chao Xu, Jiangning Zhang, Miao Hua, Qian He, Zili Yi, Yong Liu

TL;DR
This paper introduces RAFSwap, a region-aware face swapping network that combines local and global features with a face mask predictor to produce high-resolution, identity-consistent face swaps outperforming existing methods.
Contribution
The novel RAFSwap network integrates local and global feature modeling with an unsupervised face mask predictor for improved face swapping quality.
Findings
Achieves 96.70 ID retrieval accuracy, outperforming SOTA MegaFS by 5.87.
Demonstrates superior qualitative and quantitative results over state-of-the-art methods.
Effectively generates high-resolution, identity-consistent swapped faces.
Abstract
This paper presents a novel Region-Aware Face Swapping (RAFSwap) network to achieve identity-consistent harmonious high-resolution face generation in a local-global manner: \textbf{1)} Local Facial Region-Aware (FRA) branch augments local identity-relevant features by introducing the Transformer to effectively model misaligned cross-scale semantic interaction. \textbf{2)} Global Source Feature-Adaptive (SFA) branch further complements global identity-relevant cues for generating identity-consistent swapped faces. Besides, we propose a \textit{Face Mask Predictor} (FMP) module incorporated with StyleGAN2 to predict identity-relevant soft facial masks in an unsupervised manner that is more practical for generating harmonious high-resolution faces. Abundant experiments qualitatively and quantitatively demonstrate the superiority of our method for generating more identity-consistent…
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Taxonomy
TopicsFace recognition and analysis · Generative Adversarial Networks and Image Synthesis · Face and Expression Recognition
MethodsMulti-Head Attention · Attention Is All You Need · Linear Layer · Adam · Absolute Position Encodings · Position-Wise Feed-Forward Layer · Dense Connections · Label Smoothing · Dropout · Softmax
