Zihui Gao1,3*, Jia-Wang Bian2*, Guosheng Lin3, Hao Chen1†, Chunhua Shen1
1Zhejiang University, 2ByteDance Seed, 3Nanyang Technological University,
ICCV2025
Surface reconstruction and novel view rendering from sparse-view images are challenging. Signed Distance Function (SDF)-based methods struggle with fine details, while 3D Gaussian Splatting (3DGS)-based approaches lack global geometry coherence. We propose a novel hybrid method that combines the strengths of both approaches: SDF captures coarse geometry to enhance 3DGS-based rendering, while newly rendered images from 3DGS refine the details of SDF for accurate surface reconstruction. As a result, our method surpasses state-of-the-art approaches in surface reconstruction and novel view synthesis on the DTU and MobileBrick datasets.
- Release the training code.
For academic usage, this project is licensed under the 2-clause BSD License. For commercial inquiries, please contact Chunhua Shen.