Vista3D: Unravel the 3D Darkside of a Single Image
Authors: name: Qiuhong Shen; name: Xingyi Yang; name: Michael Bi Mi; name: Xinchao Wang
Published: 2024-09-18 17:59:44

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.