# MonoClothCap: Towards Temporally Coherent Clothing Capture from Monocular RGB Video

Source: [MonoClothCap: Towards Temporally Coherent Clothing Capture from Monocular RGB Video](<https://www.sota2.com/research/paper/68fa68c11e209131cea1e139>)

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

Data updated: 2025-10-25T22:44:52.991Z

Authors: Donglai Xiang, Fabian Prada, Chenglei Wu, Jessica Hodgins

Published: 2020-09-22T17:54:38.000Z

## Abstract

We present a method to capture temporally coherent dynamic clothing deformation from a monocular RGB video input. In contrast to the existing literature, our method does not require a pre-scanned personalized mesh template, and thus can be applied to in-the-wild videos. To constrain the output to a valid deformation space, we build statistical deformation models for three types of clothing: T-shirt, short pants and long pants. A differentiable renderer is utilized to align our captured shapes to the input frames by minimizing the difference in both silhouette, segmentation, and texture. We develop a UV texture growing method which expands the visible texture region of the clothing sequentially in order to minimize drift in deformation tracking. We also extract fine-grained wrinkle detail from the input videos by fitting the clothed surface to the normal maps estimated by a convolutional neural network. Our method produces temporally coherent reconstruction of body and clothing from monocular video. We demonstrate successful clothing capture results from a variety of challenging videos. Extensive quantitative experiments demonstrate the effectiveness of our method on metrics including body pose error and surface reconstruction error of the clothing.

## 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): 17.9.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2009.10711>)

[PDF](<https://arxiv.org/pdf/2009.10711.pdf>)