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.
Vista3D: Unravel the 3D Darkside of a Single Image
Vista3D framework generates 3D models from 2D images using Gaussian Splatting and disentangled implicit functions, combining 2D and 3D diffusion priors for improved quality and consistency.
- Year
- 2024
- Venue
- arXiv 2024
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- 4
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2409.12193ARXIV-DEFAULT
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