Vista3D: Unravel the 3D Darkside of a Single Image
Abstract
We embark on the age-old quest: unveiling the hidden dimensions of objects from mere glimpses of their visible parts. To address this, we present Vista3D, a framework that realizes swift and consistent 3D generation within a mere 5 minutes. At the heart of Vista3D lies a two-phase approach: the coarse phase and the fine phase. In the coarse phase, we rapidly generate initial geometry with Gaussian Splatting from a single image. In the fine phase, we extract a Signed Distance Function (SDF) directly from learned Gaussian Splatting, optimizing it with a differentiable isosurface representation. Furthermore, it elevates the quality of generation by using a disentangled representation with two independent implicit functions to capture both visible and obscured aspects of objects. Additionally, it harmonizes gradients from 2D diffusion prior with 3D-aware diffusion priors by angular diffusion prior composition. Through extensive evaluation, we demonstrate that Vista3D effectively sustains a balance between the consistency and diversity of the generated 3D objects. Demos and code will be available at https://github.com/florinshen/Vista3D.
Cite
Text
Shen et al. "Vista3D: Unravel the 3D Darkside of a Single Image." Proceedings of the European Conference on Computer Vision (ECCV), 2024. doi:10.1007/978-3-031-72670-5_23Markdown
[Shen et al. "Vista3D: Unravel the 3D Darkside of a Single Image." Proceedings of the European Conference on Computer Vision (ECCV), 2024.](https://mlanthology.org/eccv/2024/shen2024eccv-vista3d/) doi:10.1007/978-3-031-72670-5_23BibTeX
@inproceedings{shen2024eccv-vista3d,
title = {{Vista3D: Unravel the 3D Darkside of a Single Image}},
author = {Shen, Qiuhong and Yang, Xingyi and Mi, Michael Bi and Wang, Xinchao},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2024},
doi = {10.1007/978-3-031-72670-5_23},
url = {https://mlanthology.org/eccv/2024/shen2024eccv-vista3d/}
}