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Revisiting Avatar-As-Image: High-Fidelity Registration is All You Need

arxiv.org/abs/2609.11722

Updated 51 min ago · first seen 11 Sept 2026

paper_01M294H2J560W0ZEX12WM9WJY8

Published
11 Sept 2026
T1 · 51 min ago
arXiv
2609.11722
T1 · 51 min ago
Category
cs.CV
T1 · 51 min ago

Abstract

The representation of 3D clothed humans as standardized 2D UV texture and displacement maps over an underlying body model has long been studied. This compact representation is enticing as it enables pretrained image networks to process, generate, and edit 3D avatars, but is only useful if scans are accurately aligned and brought into correspondence via high-fidelity registration. This prerequisite has never been met, which we argue explains the limited quality of prior UV-based methods for clothed humans. Despite its significance, no public method produces high-fidelity SMPL(-X)+D registrations with UV texture from arbitrary clothed scans. We present AvaImg, a multi-stage optimization pipeline, to close this gap: it enforces body-inside-clothing constraint via signed winding numbers, made viable by a three-level efficiency cascade (~10x runtime reduced, ~95% storage saved), and recovers fine surface detail using coarse-to-fine displacement optimization. AvaImg outperforms all baselines in body fitting, shape estimation, and surface registration across six datasets, yielding textured registrations near-indistinguishable from scans (PSNR=34.48dB). For validation of AvaImg's Avatar-as-Image representation as imminently compatible with image foundation models, we auto-encode our UV maps via the frozen FLUX VAE. This achieves only 0.76mm added Chamfer error relative to scan and shows that the resulting maps lie within natural-image distributions, supporting the use of 2D generative priors for 3D avatar generation. Code, data, and Singularity containers will be at https://yuxuan-xue.com/avaimg.

Authors 4

Margaret Kostyrko, Yuxuan Xue, Garvita Tiwari, Gerard Pons-Moll

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Arxiv announce type
new

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

arXiv id
2609.11722

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Categories
cs.CV

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Primary category
cs.CV

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Published
11 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

51 min ago

Conflicts

None