@inproceedings{
pan2024humansplat,
title={HumanSplat: Generalizable Single-Image Human Gaussian Splatting with Structure Priors},
author={Panwang Pan and Zhuo Su and Chenguo Lin and Zhen Fan and Yongjie zhang and Zeming Li and Tingting Shen and Yadong MU and Yebin Liu},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=JBAUg7o8Yv}
}
Despite recent advancements in high-fidelity human reconstruction techniques, the requirements for densely captured images or time-consuming per-instance optimization significantly hinder their applications in broader scenarios. To tackle these issues, we present **HumanSplat**, which predicts the 3D Gaussian Splatting properties of any human from a single input image in a generalizable manner.
Specifically, HumanSplat comprises a 2D multi-view diffusion model and a latent reconstruction Transformer with human structure priors that adeptly integrate geometric priors and semantic features within a unified framework. A hierarchical loss that incorporates human semantic information is devised to achieve high-fidelity texture modeling and impose stronger constraints on the estimated multiple views. Comprehensive experiments on standard benchmarks and in-the-wild images demonstrate that HumanSplat surpasses existing state-of-the-art methods in achieving photorealistic novel-view synthesis. Project page: https://humansplat.github.io.
HumanSplat: Generalizable Single-Image Human Gaussian Splatting with Structure Priors
Panwang Pan Zhuo Su Chenguo Lin Zhen Fan Yongjie zhang Zeming Li Tingting Shen Yadong MU Yebin Liu