GaussianObject
PaidHigh-Quality 3D Object Reconstruction from Four Views with Gaussian Splatting
About GaussianObject
GaussianObject is a research framework for high-quality 3D object reconstruction from only four input images using Gaussian splatting. It addresses challenges of multi-view consistency and incomplete object information from sparse views by introducing visual hull initialization and floater elimination as structure priors, followed by a Gaussian repair model based on diffusion models that refines the representation. The framework supports both COLMAP-based and COLMAP-free (no pre-given camera poses) settings. Evaluated on MipNeRF360, OmniObject3D, OpenIllumination, and unposed image datasets, GaussianObject outperforms previous state-of-the-art methods. Published at SIGGRAPH Asia 2024 in ACM Transactions on Graphics.
Key Features
Pros & Cons
- High rendering quality from only four input images
- Works without accurate camera poses (COLMAP-free)
- Outperforms previous state-of-the-art methods on multiple challenging datasets
- Requires at least four input images (not fewer)
- Repair model training involves a self-generating strategy that adds complexity
- Currently a research framework, not a ready-to-use commercial product
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