We will update the following list after the paper is accepted.
- [2025-02-07] We have released our project page.
- We have uploaded our paper, NeuralGS on arXiv.
- Upload the code
Table 1. Quantitative results evaluated on Mip-NeRF 360, Tanks&Temples, and Deep Blending datasets. We highlight the best-performing results in bold and the second-best results in underline for all compression methods.

Table 2. Comparison of the rendering speed(FPSβ). The rendering speed of all methods is measured on our machine.

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