Vista3D: Unravel the 3D Darkside of a Single Image
<|reference_start|>Vista3D: Unravel the 3D Darkside of a Single Image: 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.<|reference_end|>
@article{shen2024vista3d:,
    title={Vista3D: Unravel the 3D Darkside of a Single Image},
    author={Qiuhong Shen, Xingyi Yang, Michael Bi Mi, Xinchao Wang},
    journal={arXiv preprint arXiv:2409.12193},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.12193},
    primaryClass={cs.CV cs.AI cs.GT cs.MM}
}