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update README.md
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wangxiaomeng030 committed Sep 23, 2024
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Expand Up @@ -189,7 +189,7 @@ usage: ds-eval [-h] --output-dir PATH --gt-mesh {None}|STR

The figure below is the algorithm pipeline. When adding a new deep-learning based SLAM algorithm, you need to register the algorithm in **input_config.py** and re-inherit and implement the functions in the **Algorithm** and **Model** classes. For details, please see [adding_a_new_algorithm ](docs/adding_a_new_algorithm.md)

![pipeline](docs/imgs/pipeline.png)
![pipeline](docs/imgs/SLAM_components.png)

### 5. Benchmark

Expand All @@ -203,16 +203,16 @@ Note: The default configuration in the algorithm is suitable for Replica. If you

| Algorithm | ATE RMSE [cm] - | PSNR+ | SSIM+ | LPIPS- | Precision [%] + | Recall [%] + | F1[%] + | Depth L1[cm] - | Acc. [cm]- | Comp. [cm]- | Comp. Ratio [<5cm %] + |
| ------------ | ------------------- | ----- | ----- | ------ | --------------- | ------------ | ------- | -------------- | -------------- | -------------- | ---------------------- |
| NICE-SLAM | 1.95 | 24.42 | 0.81 | 0.23 | 44.10 | 43.69 | 43.86 | 3.53 | 2.85 | 3.00 | 89.33 |
| NICE-SLAM* | 2.09 | 25.68 | 0.85 | 0.32 | 46.62 | 37.53 | 41.47 | 2.62 | 2.03 | 3.38 | 87.81 |
| Co-SLAM | 0.86 | 30.24 | 0.93 | 0.25 | - | - | - | 1.51 | 2.10 | 2.08 | 93.44 |
| Co-SLAM* | 1.11 | 30.34 | 0.93 | 0.24 | 80.66 | 68.79 | 74.23 | 1.63 | 1.53 | 2.90 | 89.81 |
| Vox-Fusion | 0.54 | 24.41 | 0.80 | 0.24 | 55.73 | 49.13 | 52.20 | 2.46 | 2.37 | 2.28 | 92.86 |
| Vox-Fusion* | 0.56 | 27.95 | 0.90 | 0.25 | 89.52 | 71.34 | 79.39 | 1.03 | 1.39 | 2.82 | 90.13 |
| Point-SLAM | 0.52 | 35.17 | 0.97 | 0.12 | 96.99 | 83.59 | 89.77 | 0.44 | - | - | - |
| Point-SLAM* | 0.47 | 34.10 | 0.97 | 0.10 | 99.30 | 83.78 | 90.86 | 0.38 | 1.25 | 3.12 | 88.15 |
| SplaTAM | 0.36 | 34.11 | 0.97 | 0.10 | - | - | - | - | - | - | - |
| SplaTAM* | 0.40 | 34.44 | 0.96 | 0.09 | - | - | - | - | - | - | - |
| NICE-SLAM | **1.95** | 24.42 | 0.81 | **0.23** | 44.10 | **43.69** | **43.86** | 3.53 | 2.85 | **3.00** | **89.33** |
| NICE-SLAM* | 2.09 | **25.68** | **0.85** | 0.32 | **46.62** | 37.53 | 41.47 | **2.62** | **2.03** | 3.38 | 87.81 |
| Co-SLAM | **0.86** | 30.24 | **0.93** | 0.25 | - | - | - | **1.51** | 2.10 | **2.08** | **93.44** |
| Co-SLAM* | 1.11 | **30.34** | **0.93** | **0.24** | 80.66 | 68.79 | 74.23 | 1.63 | **1.53** | 2.90 | 89.81 |
| Vox-Fusion | **0.54** | 24.41 | 0.80 | **0.24** | 55.73 | 49.13 | 52.20 | 2.46 | 2.37 | **2.28** | **92.86** |
| Vox-Fusion* | 0.56 | **27.95** | **0.90** | 0.25 | **89.52** | **71.34** | **79.39** | **1.03** | **1.39** | 2.82 | 90.13 |
| Point-SLAM | 0.52 | **35.17** | **0.97** | 0.12 | 96.99 | 83.59 | 89.77 | 0.44 | - | - | - |
| Point-SLAM* | **0.47** | 34.10 | **0.97** | **0.10** | **99.30** | **83.78** | **90.86** | **0.38** | 1.25 | 3.12 | 88.15 |
| SplaTAM | **0.36** | 34.11 | **0.97** | 0.10 | - | - | - | - | - | - | - |
| SplaTAM* | 0.40 | **34.44** | 0.96 | **0.09** | - | - | - | - | - | - | - |
| DPVO* | 0.31 | - | - | - | - | - | - | - | - | - | - |
| NeuralRecon* | - | - | - | - | 13.29 | 7.43 | 9.51 | - | 5.87 | 19.36 | 38.13 |

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