HumanDreamer-X: Photorealistic Single-image Human Avatars Reconstruction
  via Gaussian Restoration
Single-image human reconstruction is vital for digital human modeling
applications but remains an extremely challenging task. Current approaches rely
on generative models to synthesize multi-view images for subsequent 3D
reconstruction and animation. However, directly generating multiple views from
a single human image suffers from geometric inconsistencies, resulting in
issues like fragmented or blurred limbs in the reconstructed models. To tackle
these limitations, we introduce HumanDreamer-X, a novel framework that
integrates multi-view human generation and reconstruction into a unified
pipeline, which significantly enhances the geometric consistency and visual
fidelity of the reconstructed 3D models. In this framework, 3D Gaussian
Splatting serves as an explicit 3D representation to provide initial geometry
and appearance priority. Building upon this foundation, HumanFixer is
trained to restore 3DGS renderings, which guarantee photorealistic results.
Furthermore, we delve into the inherent challenges associated with attention
mechanisms in multi-view human generation, and propose an attention modulation
strategy that effectively enhances geometric details identity consistency
across multi-view. Experimental results demonstrate that our approach markedly
improves generation and reconstruction PSNR quality metrics by 16.45% and
12.65%, respectively, achieving a PSNR of up to 25.62 dB, while also showing
generalization capabilities on in-the-wild data and applicability to various
human reconstruction backbone models.
67f364118188d683931bec4a
Boyuan Wang
67f364118188d683931bec4b
Runqi Ouyang
67f364118188d683931bec4c
Xiaofeng Wang
claimed_verified
2025-04-08T14:24:59.872Z
6426616ea5ec4a5cbc535634
https://cdn-avatars.huggingface.co/v1/production/uploads/6426616ea5ec4a5cbc535634/hH6JsxnXeakH3mBTeNNmO.jpeg
JeffWang
user
Jeff-Wang
67f364118188d683931bec4d
Zheng Zhu
extracted_pending
2025-04-07T05:35:15.515Z
656e9b562cd7a3e348011d26
/avatars/bcca51bdc27c664f8f132420e6ed99fa.svg
Zheng Zhu
user
ZhengZhu
67f364118188d683931bec4e
Guosheng Zhao
67f364118188d683931bec4f
Chaojun Ni
67f364118188d683931bec50
Guan Huang
67f364118188d683931bec51
Lihong Liu
67f364118188d683931bec52
Xingang Wang
HumanDreamer-X: Photorealistic Single-image Human Avatars Reconstruction
  via Gaussian Restoration
Single-image human reconstruction is vital for digital human modeling
applications but remains an extremely challenging task. Current approaches rely
on generative models to synthesize multi-view images for subsequent 3D
reconstruction and animation. However, directly generating multiple views from
a single human image suffers from geometric inconsistencies, resulting in
issues like fragmented or blurred limbs in the reconstructed models. To tackle
these limitations, we introduce HumanDreamer-X, a novel framework that
integrates multi-view human generation and reconstruction into a unified
pipeline, which significantly enhances the geometric consistency and visual
fidelity of the reconstructed 3D models. In this framework, 3D Gaussian
Splatting serves as an explicit 3D representation to provide initial geometry
and appearance priority. Building upon this foundation, HumanFixer is
trained to restore 3DGS renderings, which guarantee photorealistic results.
Furthermore, we delve into the inherent challenges associated with attention
mechanisms in multi-view human generation, and propose an attention modulation
strategy that effectively enhances geometric details identity consistency
across multi-view. Experimental results demonstrate that our approach markedly
improves generation and reconstruction PSNR quality metrics by 16.45% and
12.65%, respectively, achieving a PSNR of up to 25.62 dB, while also showing
generalization capabilities on in-the-wild data and applicability to various
human reconstruction backbone models.
A novel framework, HumanDreamer-X, enhances single-image human reconstruction through unified 3D Gaussian Splatting and HumanFixer, improving PSNR and handling in-the-wild data.
HumanDreamer-X HumanFixer 3D Gaussian Splatting multi-view human generation attention modulation photorealistic results PSNR quality metrics