Astrolabe: Spherical-Map Guidance Across Diffusion Pipelines for Full-Body Capture from Unconstrained Images 文章

ArXiv CS.CV2026-08-04PAPERen作者: Shuliang Zhu, Qi Wang, Ryugo Morita, Jinjia Zhou

详细信息

来源站点
ArXiv CS.CV
作者
Shuliang Zhu, Qi Wang, Ryugo Morita, Jinjia Zhou
文章类型
PAPER
语言
en
发布日期
2026-08-04

摘要

arXiv:2608.01276v1 Announce Type: new Abstract: Full-body capture from unconstrained photographs requires global correspondence across arbitrary views, poses, crops, and occlusions. Yet pose, geometry, and foundation features estimated in this setting are too unreliable for dense matching or appearance transfer, while diffusion rectifiers and optimization pipelines expose no common interface for consuming such uncertain correspondence. Our insight is that correspondence need not be locally accurate: its coarse viewpoint and body layout can still organize how a diffusion prior adapts and guides reconstruction. We introduce \emph{Astrolabe}, a host-portable adapter built on frozen viewpoint-guided spherical maps (SPH). A fixed bounded transform converts SPH into a spatial noise shift, which is matched during prior adaptation and reused during downstream denoising or score-distillation guidance in both pipeline categories.

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