S-PIFu: Integrating Parametric Human Models with PIFu for Single-view Clothed Human Reconstruction

Kennard Chan, Guosheng Lin, Haiyu Zhao, Weisi Lin

Keywords: Single-view clothed human reconstruction, parametric human body models, pixel-aligned implicit models

TL;DR: Combining a pixel-aligned implicit model with a parametric human body model using ray-based sampling

Abstract: We present three novel strategies to incorporate a parametric body model into a pixel-aligned implicit model for single-view clothed human reconstruction. Firstly, we introduce ray-based sampling, a novel technique that transforms a parametric model into a set of highly informative, pixel-aligned 2D feature maps. Next, we propose a new type of feature based on blendweights. Blendweight-based labels serve as soft human parsing labels and help to improve the structural fidelity of reconstructed meshes. Finally, we show how we can extract and capitalize on body part orientation information from a parametric model to further improve reconstruction quality. Together, these three techniques form our S-PIFu framework, which significantly outperforms state-of-the-arts methods in all metrics. Our code is available at https://github.com/kcyt/SPIFu.