BCNet: Learning Body and Cloth Shape from A Single Image

April 01, 2020 · Entered Twilight · 🏛 European Conference on Computer Vision

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Repo contents: README.md, body_garment_dataset, code, environment.yaml, images, smpl_pytorch

Authors Boyi Jiang, Juyong Zhang, Yang Hong, Jinhao Luo, Ligang Liu, Hujun Bao arXiv ID 2004.00214 Category cs.CV: Computer Vision Cross-listed cs.GR Citations 190 Venue European Conference on Computer Vision Repository https://github.com/jby1993/BCNet ⭐ 113 Last Checked 1 month ago

Abstract

In this paper, we consider the problem to automatically reconstruct garment and body shapes from a single near-front view RGB image. To this end, we propose a layered garment representation on top of SMPL and novelly make the skinning weight of garment independent of the body mesh, which significantly improves the expression ability of our garment model. Compared with existing methods, our method can support more garment categories and recover more accurate geometry. To train our model, we construct two large scale datasets with ground truth body and garment geometries as well as paired color images. Compared with single mesh or non-parametric representation, our method can achieve more flexible control with separate meshes, makes applications like re-pose, garment transfer, and garment texture mapping possible. Code and some data is available at https://github.com/jby1993/BCNet.