Unwarping the Lens: A Physics-Grounded Approach to Video Glasses Removal
High-fidelity removal of eyeglasses from video is a major challenge in facial attribute editing, as the underlying facial geometry is often obscured by complex refractive distortions and view-dependent specular reflections. While large-scale generative priors have shown promise in eye-glasses removal via static image inpainting, they often lack the structural constraints necessary to maintain identity, expression, and pose, leading to visible "identity drift" in both static images and dynamic sequences. In this paper, we propose a novel transfer framework that addresses the stochastic nature of generative priors. Our pipeline first extracts high-fidelity synthetic face images from a comme...
| Authors | Radim Spetlik, David Futschik, Radek Danecek et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 August 2026 |
| Last updated at source | 20 August 2026 |
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