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Official implementation of "NeuralGS: Bridging Neural Fields and 3D Gaussian Splatting for Compact 3D Representation"

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Implemetation of Bridging Neural Fields and 3D Gaussian Splatting for Compact 3D Representation.

🗓️ TODO

We will update the following list after the paper is accepted.

🍭 Novel Synthesis Results

🌅 Qualitative comparison

📊 Quantitative comparison

Table 1. Quantitative results evaluated on Mip-NeRF 360, Tanks&Temples, and Deep Blending datasets. We highlight the best-performing results in red and the second-best results in yellow for all compression methods Compression Pipeline
Table 2

Table 2. Quantitative results of the proposed method evaluated on the NeRF-Synthetic dataset. We highlight the best-performing results in red and the second-best results in yellow for all compression methods.

Table 3

Table 3. Performance comparison with 3DGS. Rendering FPS and model size (MB) are reported. The rendering speed of both methods is measured on our machine.

Table 4

Table 4. Quantitative ablation study on the Deep Blending dataset by progressively adding our proposed improvement.

🙏 Acknowledgements

This source code is derived from multiple sources, in particular: gaussian-splatting. We thank the authors for releasing their code.

To be contunied...

🤝 Contributors

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Official implementation of "NeuralGS: Bridging Neural Fields and 3D Gaussian Splatting for Compact 3D Representation"

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