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VastGaussian

Unofficial implementation of Vast 3D Gaussians for Large Scene Reconstruction

#computer vision
#Open source projects
#3D scene reconstruction
#Graphics
VastGaussian

Product Details

VastGaussian is an open source project for 3D scene reconstruction, which simulates the geometry and appearance information of large scenes by using 3D Gaussian. This project was implemented by the author from scratch and may have some errors, but it provides a new attempt in the field of 3D scene reconstruction. The main advantages of the project include the ability to handle large data sets, as well as improvements to the original 3DGS project to make it easier to understand and use.

Main Features

1
Camera-position-based region division implements region division based on camera position
2
Position-based data selection implements position-based data selection
3
Visibility-based camera selection implements visibility-based camera selection
4
Coverage-based point selection implements coverage-based point selection
5
Decoupled Appearance Modeling realizes appearance decoupling modeling
6
Seamless Merging enables seamless merging
7
Parallel training of m√ón regions on a single GPU implements parallel training of multiple regions on a single GPU

How to Use

1
Clone or download the VastGaussian project locally
2
Set up the environment according to the project documentation, including installing necessary dependent libraries
3
Adjust the parameters in the arguments/parameters.py file to suit your dataset and needs
4
Use the train_vast.py file to start training the VastGaussian model
5
Use the provided scripts or command line tools for model evaluation and use

Target Users

The target audience is researchers and developers in the fields of 3D scene reconstruction, computer vision and graphics. VastGaussian is suitable for them because it provides a new 3D scene reconstruction method that can handle large-scale data sets and improves on the original 3DGS project to make it easier to understand and use.

Examples

Application on UrbanScene3D dataset

Application on Mill-19 data set

Application on tandt_db data set

Quick Access

Visit Website →

Categories

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› AI model inference training
› AI 3D tools

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