Sparc3D: Sparse Representation and Construction
for High-Resolution 3D Shapes Modeling
> We introduce **Sparc3D**, a unified framework that combines a sparse deformable marching cubes representation **Sparcubes** with a novel encoder **Sparconv-VAE**. Sparcubes converts raw meshes into high-resolution (1024³) surfaces with arbitrary topology by scattering signed distance and deformation fields onto a sparse cube, allowing differentiable optimization. Sparconv-VAE is the first modality-consistent variational autoencoder built entirely upon sparse convolutional networks, enabling efficient and near-lossless 3D reconstruction suitable for high-resolution generative modeling through latent diffusion.
## Citation
If you find this work useful, please cite:
```bibtex
@article{li2025sparc3d,
title = {Sparc3D: Sparse Representation and Construction for High-Resolution 3D Shapes Modeling},
author = {Li, Zhihao and Wang, Yufei and Zheng, Heliang and Luo, Yihao and Wen, Bihan},
journal = {arXiv preprint arXiv:2505.14521},
year = {2025}
}