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AlbumVSR: Identity-Preserving Face Video Super-Resolution from a Personal Photo Album
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Nianyao Du, Xijun Wang, Stanley H. Chan

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ResearcharXiv cs.CV

AlbumVSR: Identity-Preserving Face Video Super-Resolution from a Personal Photo Album

arXiv:2610.39001v1 Announce Type: new Abstract: Severe blur, downsampling, noise, and compression can erase the identity cues needed to faithfully restore a person's face. We therefore use photographs of the same person as an external source of identity. AlbumVSR conditions a frozen, one-step streaming diffusion transformer on a personal album. We use four MagFace/CLIP set tokens to encode the album, and 64 texture tokens which come from a fused UV atlas rendered at the current window's estimated face pose. These tokens are appended to the transformer's cached cross-attention context. On an identity-disjoint VoxCeleb2 benchmark with heavy synthetic degradation, AlbumVSR raises ArcFace similarity to the ground truth from 0.586 to 0.670 and face PSNR from 24.98 to 26.71 dB. On the 91 test identities, its mean identity similarity is higher than that of all 14 baselines.

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This story was published by arXiv cs.CV and written by Nianyao Du, Xijun Wang, Stanley H. Chan. SyncAI.news shows a preview; the complete article is on the publisher's site.

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