无需训练，通过波形结构约束和频率修正实现高保真人脸修复
WaveFreqAnchor: Wave-Structural Anchoring and Frequency Correction Diffusion for Training-Free Face Restoration
- 利用各向异性波响应一致性约束面部结构
- 通过相位替换修正逆扩散中的频率偏差
- 适合处理复杂退化下的真实人脸修复任务
基于扩散模型的人脸修复通过调整预训练模型的采样轨迹取得了显著进展。然而，现有方法在逆扩散过程中约束不足，导致严重退化下身份相关结构漂移和保真度下降。为此，我们提出WaveFreqAnchor，一种无需训练的框架，包含波-结构锚定与频率修正扩散。具体地，锚定空间波结构引导（ASWG）通过各向异性波响应一致性约束面部结构；多尺度小波-傅里叶注入（MWFI）通过替换低频子带相位，对齐预测与观测结果，纠正逆扩散中累积的不一致。针对真实场景，引入子带高频增强（SHE），对预测的高频子带进行有界、空间掩码的精细化修复，以恢复未知复合退化下的精细面部细节。上述设计共同有效保留面部身份，同时恢复清晰逼真的面部特征。大量实验表明，本方法持续优于现有方法，在高质量与高保真度方面表现优异。
原文摘要 · Abstract (English)
Diffusion-based face restoration that adjusts the sampling trajectory of pre-trained diffusion models has achieved remarkable progress. However, existing approaches provide insufficient constraints during reverse diffusion, causing identity-related structural drift and degraded fidelity under severe degradations. To address this, we propose WaveFreqAnchor, a training-free framework based on Wave-Structural Anchoring and Frequency Correction Diffusion. Specifically, Anchor-Space Wave-Structural Guidance (ASWG) constrains facial structures through anisotropic wave-response consistency, while Multi-scale Wavelet-Fourier Injection (MWFI) aligns the predicted low-frequency subband with the observation by replacing its phase, correcting inconsistencies accumulated during reverse diffusion. For real-world scenes, we further introduce Subband High-Frequency Enhancement (SHE), which performs bounded, spatially masked refinement on the predicted high-frequency subbands to recover fine facial details under unknown compound degradations. Together, these designs effectively preserve facial identity while restoring sharp and realistic facial details. Extensive experiments show that our method consistently outperforms existing methods, achieving high-quality and high-fidelity face restoration.
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