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* test table

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AdamRashid96 authored Feb 22, 2024
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4 changes: 4 additions & 0 deletions README.md
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![Teaser](/docs/source/imgs/training.gif?raw=true)

## Evaluation
A full evalaution of Nerfstudio's implementation of Gaussian Splatting against the original Inria method can be found [here](https://docs.gsplat.studio/tests/eval.html).


## Installation

**Dependence**: Please install [Pytorch](https://pytorch.org/get-started/locally/) first.
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Evaluation
===================================

We evaluate our implementation of Gaussian Splatting (`Splatfacto <https://github.com/nerfstudio-project/nerfstudio/tree/1d070f5625ab42d0a0dff1ad4c6cfb655aab6d3d>`_) on the Mip-NeRF 360 dataset, benchmarking it against the original `Inria <https://github.com/graphdeco-inria/gaussian-splatting/tree/2eee0e26d2d5fd00ec462df47752223952f6bf4e>`_ method. We evaluate all methods with the same resolution (2x downscale) and COLMAP params/undistortion, and we report results at 7,000 and 30,000 steps. All evaluations were executed on an NVIDIA RTX 4090 GPU.

.. list-table:: **Time**
:widths: 10 10 10 10 10 10 10 10 10 10
:header-rows: 1

* -
- Bicycle
- Bonsai
- Counter
- Flowers
- Garden
- Kitchen
- Stump
- Treehill
- Avg
* - inria-7k
- 3:34
- 3:27
- 3:05
- 3:02
- 3:51
- 4:00
- 3:25
- 2:53
- 3:24
* - splfacto-7k
- 2:36
- 2:18
- 2:06
- 2:14
- 2:49
- 2:17
- 2:24
- 2:23
- 2:23
* - splfacto-big-7k
- 3:41
- 3:11
- 2:59
- 2:51
- 3:51
- 3:15
- 2:49
- 2:47
- 3:10
* - inria-30k
- 25:07
- 14:37
- 15:24
- 17:32
- 24:03
- 19:02
- 20:25
- 18:02
- 19:17
* - splfacto-30k
- 18:03
- 10:13
- 9:07
- 13:25
- 14:58
- 10:02
- 15:15
- 16:56
- 13:30
* - splfacto-big-30k
- 31:05
- 13:32
- 13:27
- 22:44
- 26:03
- 16:16
- 21:58
- 25:26
- 21:19

.. list-table:: **PSNR**
:widths: 10 10 10 10 10 10 10 10 10 10
:header-rows: 1

* -
- Bicycle
- Bonsai
- Counter
- Flowers
- Garden
- Kitchen
- Stump
- Treehill
- Avg
* - inria-7k
- 24.11
- 29.49
- 27.16
- 20.54
- 26.53
- 29.02
- 26.74
- 22.50
- 25.76
* - splatfacto-7k
- 22.99
- 29.45
- 26.92
- 20.33
- 25.76
- 28.48
- 24.59
- 21.91
- 25.05
* - splatfacto-big-7k
- 23.66
- 29.69
- 27.01
- 20.73
- 26.58
- 28.82
- 25.69
- 22.11
- 25.54
* - inria-30k
- 25.61
- 31.89
- 28.96
- 21.56
- 27.60
- 31.30
- 25.89
- 22.07
- 26.86
* - splatfacto-30k
- 24.99
- 32.14
- 28.72
- 21.54
- 27.31
- 31.18
- 25.64
- 22.28
- 26.73
* - splatfacto-big-30k
- 25.7
- 32.23
- 28.95
- 21.96
- 27.83
- 31.6
- 26.7
- 22.38
- 27.17


.. list-table:: **LPIPS**
:widths: 10 10 10 10 10 10 10 10 10 10
:header-rows: 1

* -
- Bicycle
- Bonsai
- Counter
- Flowers
- Garden
- Kitchen
- Stump
- Treehill
- Avg
* - inria-7k
- 0.31
- 0.24
- 0.25
- 0.42
- 0.16
- 0.16
- 0.28
- 0.42
- 0.28
* - splfacto-7k
- 0.31
- 0.16
- 0.21
- 0.44
- 0.15
- 0.14
- 0.28
- 0.45
- 0.27
* - splfacto-big-7k
- 0.28
- 0.16
- 0.20
- 0.42
- 0.12
- 0.13
- 0.23
- 0.43
- 0.24
* - inria-30k
- 0.21
- 0.21
- 0.20
- 0.34
- 0.11
- 0.13
- 0.22
- 0.32
- 0.22
* - splfacto-30k
- 0.18
- 0.13
- 0.17
- 0.34
- 0.09
- 0.10
- 0.18
- 0.32
- 0.19
* - splfacto-big-30k
- 0.15
- 0.13
- 0.15
- 0.31
- 0.07
- 0.09
- 0.15
- 0.28
- 0.17

.. list-table:: **SSIM**
:widths: 10 10 10 10 10 10 10 10 10 10
:header-rows: 1

* -
- Bicycle
- Bonsai
- Counter
- Flowers
- Garden
- Kitchen
- Stump
- Treehill
- Avg
* - inria-7k
- 0.69
- 0.92
- 0.88
- 0.53
- 0.83
- 0.90
- 0.73
- 0.59
- 0.76
* - splfacto-7k
- 0.65
- 0.92
- 0.88
- 0.53
- 0.85
- 0.90
- 0.68
- 0.58
- 0.74
* - splfacto-big-7k
- 0.69
- 0.92
- 0.88
- 0.55
- 0.84
- 0.90
- 0.74
- 0.61
- 0.77
* - inria-30k
- 0.78
- 0.94
- 0.91
- 0.61
- 0.87
- 0.92
- 0.77
- 0.63
- 0.80
* - splfacto-30k
- 0.75
- 0.94
- 0.90
- 0.60
- 0.85
- 0.92
- 0.73
- 0.63
- 0.79
* - splfacto-big-30k
- 0.78
- 0.94
- 0.91
- 0.63
- 0.88
- 0.93
- 0.77
- 0.64
- 0.81

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