263-3d-gaussian-splatting-for-real-time-radiance-field-rendering
https://github.com/szu-advtech-2023/263-3d-gaussian-splatting-for-real-time-radiance-field-rendering
Science Score: 18.0%
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (4.4%) to scientific vocabulary
Last synced: 10 months ago
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Repository
Basic Info
- Host: GitHub
- Owner: SZU-AdvTech-2023
- Language: Python
- Default Branch: main
- Size: 1.55 MB
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- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 2 years ago
· Last pushed over 2 years ago
Metadata Files
Citation
https://github.com/SZU-AdvTech-2023/263-3D-Gaussian-Splatting-for-Real-Time-Radiance-Field-Rendering/blob/main/
# Gaussion_splatting ## Installation ``` # create virtual environment conda create -yn gs python=3.9 pip conda activate gs # install the PyTorch first, you must install the one match to the version of your nvcc (nvcc --version) # for cuda 11.3 pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113 # install other requirements pip install -r requirements.txt ``` ## Download the Blender dataset and unzip it into the 'dataset' directory. ## Train ``` python train.py ``` ## Evaluation ``` python eval.py ``` ## Render a video. ``` python render.py ```
Owner
- Name: SZU-AdvTech-2023
- Login: SZU-AdvTech-2023
- Kind: organization
- Repositories: 1
- Profile: https://github.com/SZU-AdvTech-2023
Citation (citation.txt)
@article{REPO263,
author = {Kerbl, Bernhard and Kopanas, Georgios and Leimk{\"u}hler, Thomas and Drettakis, George},
journal = "ACM Transactions on Graphics",
number = "4",
title = "{3D Gaussian Splatting for Real-Time Radiance Field Rendering}",
volume = "42",
year = "2023"
}