# Tex2Shape: Detailed Full Human Body Geometry From a Single Image

Source: [Tex2Shape: Detailed Full Human Body Geometry From a Single Image](<https://www.sota2.com/research/paper/68fa66591e209131cea0fae6>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:47:30.843Z

Authors: Thiemo Alldieck, Gerard Pons-Moll, Christian Theobalt, Marcus Magnor

Published: 2019-04-18T09:10:20.000Z

## Abstract

We present a simple yet effective method to infer detailed full human body shape from only a single photograph. Our model can infer full-body shape including face, hair, and clothing including wrinkles at interactive frame-rates. Results feature details even on parts that are occluded in the input image. Our main idea is to turn shape regression into an aligned image-to-image translation problem. The input to our method is a partial texture map of the visible region obtained from off-the-shelf methods. From a partial texture, we estimate detailed normal and vector displacement maps, which can be applied to a low-resolution smooth body model to add detail and clothing. Despite being trained purely with synthetic data, our model generalizes well to real-world photographs. Numerous results demonstrate the versatility and robustness of our method.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [3D Human Reconstruction on MonoPerfCap Pablo sequence](<https://www.sota2.com/research/sota/3d-human-reconstruction-on-monoperfcap-pablo-sequence.md>): 3D human reconstruction; MonoPerfCap Pablo sequence; 3D Chamfer Distance (cm): 27.7.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1904.08645>)

[PDF](<https://arxiv.org/pdf/1904.08645.pdf>)