IConFace: Identity-Structure Asymmetric Conditioning for Unified Reference-Aware Face Restoration
Axi Niu, Jinyang Zhang, Senyan Qing
TLDR
IConFace introduces a unified framework for face restoration, using identity-structure asymmetric conditioning to leverage references or perform no-reference restoration.
Key contributions
- Unified framework for both reference-aware and no-reference face restoration.
- Employs identity-structure asymmetric conditioning for balanced input use.
- Distills references into a global AdaFace identity anchor for image-only modulation.
- Reinforces degraded image as spatial structure anchor with low-rank residuals.
Why it matters
This paper addresses the challenge of blind face restoration under severe degradation by proposing a unified model. It effectively leverages same-identity references when available while maintaining quality for no-reference cases, improving identity consistency and detail recovery.
Original Abstract
Blind face restoration is highly ill-posed under severe degradation, where identity-critical details may be missing from the degraded input. Same-identity references reduce this ambiguity, but mismatched pose, expression, illumination, age, makeup, or local facial states can lead to overuse of reference appearance. We propose \textbf{IConFace}, a unified reference-aware and no-reference framework with identity--structure asymmetric conditioning. References are distilled into a norm-weighted global AdaFace identity anchor for image-only modulation, while the degraded image is reinforced as the spatial structure anchor through low-rank residuals and block-wise degraded cross-attention with two-route memory. The resulting single checkpoint exploits references when available and falls back to no-reference restoration when absent, improving identity consistency, fine-detail recovery, and degraded-only restoration quality in a unified model.
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