HumanDreamer-X: Photorealistic Single-image Human Avatars Reconstruction via Gaussian Restoration

Understand

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 \textbf{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.