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feat(BEVFusion): release BEVFusion 2.7.1_opt #211

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198 changes: 197 additions & 1 deletion projects/BEVFusion/docs/BEVFusion-L/v2/j6gen2_base.md
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- **Grid Size:** [1440, 1440, 40]
- **With Intensity**

### Evaluation Environment

> Please note that BEVFusion-LiDAR J6Gen2_Base/2.7.1_opt was evaluated on TensorRT using a mid-range NVIDIA Ada-generation GPU, while CenterPoint J6Gen2_Base/2.7.1 and CenterPoint J6Gen2_Base/2.6.1 were evaluated in PyTorch.

### Testing Datasets

- **Total Frames: 5,179**
Expand Down Expand Up @@ -64,7 +68,8 @@

| Model version | mAP | mAPH | car<br>(64,520) | truck<br>(6,947) | bus<br>(2,275) | bicycle<br>(1,379) | pedestrian<br>(19,421) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.8828 | 0.8387 | 0.9022 | 0.8627 | 0.9440 | 0.8483 | 0.8569 |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.8824 | 0.8390 | 0.9021 | 0.8626 | 0.9419 | 0.8489 | 0.8567 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.8828 | 0.8387 | 0.9022 | 0.8627 | 0.9440 | 0.8483 | 0.8569 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.8810 | 0.8380 | 0.8873 | 0.8586 | 0.9476 | 0.8583 | 0.8534 |

</details>
Expand All @@ -74,6 +79,7 @@

| Model version | mAP | mAPH | car<br>(58,562) | truck<br>(5,101) | bus<br>(2,078) | bicycle<br>(758) | pedestrian<br>(10,283) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.7187 | 0.6614 | 0.8187 | 0.6840 | 0.8252 | 0.5866 | 0.6791 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.7193 | 0.6620 | 0.8197 | 0.6856 | 0.8249 | 0.5862 | 0.6801 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.7032 | 0.6483 | 0.7876 | 0.6830 | 0.7911 | 0.5802 | 0.6741 |

Expand All @@ -84,6 +90,7 @@

| Model version | mAP | mAPH | car<br>(20,371) | truck<br>(3,172) | bus<br>(376) | bicycle<br>(155) | pedestrian<br>(2,794) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.5221 | 0.4755 | 0.6798 | 0.5176 | 0.5396 | 0.4170 | 0.4565 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.5223 | 0.4757 | 0.6814 | 0.5181 | 0.5381 | 0.4165 | 0.4573 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.4938 | 0.4494 | 0.6564 | 0.5192 | 0.3777 | 0.4406 | 0.4752 |

Expand All @@ -94,6 +101,7 @@

| Model version | mAP | mAPH | car<br>(143,453) | truck<br>(15,220) | bus<br>(4,729) | bicycle<br>(2,292) | pedestrian<br>(32,498) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.7990 | 0.7487 | 0.8505 | 0.7431 | 0.8714 | 0.7493 | 0.7807 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.7990 | 0.7487 | 0.8508 | 0.7435 | 0.8711 | 0.7487 | 0.7809 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.7903 | 0.7413 | 0.8266 | 0.7409 | 0.8510 | 0.7541 | 0.7790 |

Expand All @@ -116,6 +124,7 @@

| Model version | mAP | mAPH | car<br>(14,883) | truck<br>(1,193) | bus<br>(336) | bicycle<br>(740) | pedestrian<br>(5,059) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.8939 | 0.8391 | 0.9231 | 0.8895 | 0.9514 | 0.8273 | 0.8783 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.8947 | 0.8393 | 0.9231 | 0.8893 | 0.9564 | 0.8264 | 0.8782 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.8985 | 0.8484 | 0.9087 | 0.8974 | 0.9636 | 0.8447 | 0.8780 |

Expand All @@ -126,6 +135,7 @@

| Model version | mAP | mAPH | car<br>(10,994) | truck<br>(1,011) | bus<br>(143) | bicycle<br>(463) | pedestrian<br>(3,754) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.7679 | 0.7088 | 0.8568 | 0.7654 | 0.8723 | 0.5970 | 0.7481 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.7679 | 0.7089 | 0.8567 | 0.7666 | 0.8723 | 0.5955 | 0.7485 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.7475 | 0.6925 | 0.8317 | 0.7758 | 0.7910 | 0.5959 | 0.7433 |

Expand All @@ -136,6 +146,7 @@

| Model version | mAP | mAPH | car<br>(3,018) | truck<br>(602) | bus<br>(60) | bicycle<br>(85) | pedestrian<br>(1,121) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.5929 | 0.5375 | 0.7246 | 0.6600 | 0.6413 | 0.3893 | 0.5496 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.5924 | 0.5370 | 0.7238 | 0.6616 | 0.6305 | 0.3964 | 0.5497 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.5636 | 0.5191 | 0.7125 | 0.6383 | 0.4781 | 0.4293 | 0.5595 |

Expand All @@ -146,6 +157,7 @@

| Model version | mAP | mAPH | car<br>(28,895) | truck<br>(2,806) | bus<br>(539) | bicycle<br>(1,288) | pedestrian<br>(9,934) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.8261 | 0.7675 | 0.8885 | 0.8045 | 0.8988 | 0.7338 | 0.8051 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.8267 | 0.7675 | 0.8888 | 0.8055 | 0.9009 | 0.7334 | 0.8051 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.8198 | 0.7666 | 0.8690 | 0.8052 | 0.8756 | 0.7455 | 0.8036 |

Expand Down Expand Up @@ -174,6 +186,7 @@

| Model version | mAP | mAPH | car<br>(49,637) | truck<br>(5,754) | bus<br>(1,939) | bicycle<br>(639) | pedestrian<br>(14,362) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.8833 | 0.8429 | 0.8941 | 0.8571 | 0.9386 | 0.8776 | 0.8492 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.8836 | 0.8431 | 0.8942 | 0.8569 | 0.9393 | 0.8780 | 0.8494 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.8788 | 0.8368 | 0.8813 | 0.8505 | 0.9427 | 0.8749 | 0.8448 |

Expand All @@ -184,6 +197,7 @@

| Model version | mAP | mAPH | car<br>(47,568) | truck<br>(4,090) | bus<br>(1,935) | bicycle<br>(295) | pedestrian<br>(6,529) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.7035 | 0.6484 | 0.8111 | 0.6651 | 0.8227 | 0.5784 | 0.6402 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.7040 | 0.6488 | 0.8118 | 0.6662 | 0.8221 | 0.5781 | 0.6417 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.6864 | 0.6344 | 0.7772 | 0.6609 | 0.7913 | 0.5671 | 0.6357 |

Expand All @@ -194,6 +208,7 @@

| Model version | mAP | mAPH | car<br>(17,353) | truck<br>(2,570) | bus<br>(316) | bicycle<br>(70) | pedestrian<br>(1,673) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.5020 | 0.4563 | 0.6719 | 0.4839 | 0.5176 | 0.4435 | 0.3932 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.5030 | 0.4572 | 0.6739 | 0.4847 | 0.5186 | 0.4430 | 0.3948 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.4766 | 0.4309 | 0.6465 | 0.4903 | 0.3618 | 0.4627 | 0.4214 |

Expand All @@ -204,6 +219,7 @@

| Model version | mAP | mAPH | car<br>(114,558) | truck<br>(12,414) | bus<br>(4,190) | bicycle<br>(1,004) | pedestrian<br>(22,564) |
| :---- | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| BEVFusion-LiDAR j6gen2_base/2.7.1_opt | 0.7958 | 0.7471 | 0.8404 | 0.7292 | 0.8680 | 0.7709 | 0.7703 |
| BEVFusion-LiDAR j6gen2_base/2.7.1 | 0.7958 | 0.7472 | 0.8408 | 0.7294 | 0.8673 | 0.7710 | 0.7706 |
| BEVFusion-LiDAR j6gen2_base/2.6.1 | 0.7851 | 0.7375 | 0.8166 | 0.7262 | 0.8481 | 0.7661 | 0.7687 |

Expand All @@ -213,6 +229,186 @@

## Release


### BEVFusion-LiDAR J6Gen2_base/2.7.1_opt

<details>
<summary> Changes </summary>

Optimized the ONNX model and TensorRT plugin from `BEVFusion-LiDAR base/2.7.1` for faster inference, reducing BEVFusion-L latency by ~15%. The speedup comes from three changes to the sparse convolution backbone:

- **Disable Sort**: skip sorting in `GetIndicePairsImplicitGemm`.
- **SparseConv + BatchNorm fusion**: fold BatchNorm into the preceding sparse convolution.
- **ImplicitGemm + ReLU fusion**: fuse the ReLU activation into the implicit GEMM kernel.

> **Note**: The optimized ONNX requires the latest `autoware.universe` to run correctly.
</details>

<details>
<summary> Artifacts </summary>

- Deployed onnx and ROS parameter files (for internal)
- [WebAuto](https://evaluation.ci.tier4.jp/evaluation/mlpackages/46f8188d-e3be-4f2f-b989-fd27002610d7/releases/bf274dd7-e1d0-49d7-ba3a-8c9c66d05c00?project_id=zWhWRzei)
- [model-zoo](https://download.autoware-ml-model-zoo.tier4.jp/autoware-ml/models/bevfusion/bevfusion-l/j6gen2_base/v2.7.1_opt/deployment.zip)
- [Google drive](https://drive.google.com/file/d/1cuGSnyBu_UdF5nPx6sUg-WcioXtQfFLW/view?usp=drive_link)
- Logs (for internal)
- [model-zoo](https://download.autoware-ml-model-zoo.tier4.jp/autoware-ml/models/bevfusion/bevfusion-l/j6gen2_base/v2.7.1_opt/logs.zip)
- [Google drive](https://drive.google.com/file/d/1KZD_UEv8eMubyRHcWtUdznoUpPM30PF_/view?usp=drive_link)
- Pytorch Best checkpoints:
- [model-zoo](https://download.autoware-ml-model-zoo.tier4.jp/autoware-ml/models/bevfusion/bevfusion-l/j6gen2_base/v2.7.1_opt/best_epoch_28.pth)
- [Google drive](https://drive.google.com/file/d/1Ss1UE5TAK_1ZKqUpMRKQ6R_8BhCYm5Eo/view?usp=drive_link)
</details>

<details>
<summary> Evaluation </summary>

**J6Gen2_base Datasets (5,179 frames)**:

- j6gen2 (3,951 frames): db_j6gen2_v1 + db_j6gen2_v2 + db_j6gen2_v3 + db_j6gen2_v4 + db_j6gen2_v5 + db_j6gen2_v6 + db_j6gen2_v7 + db_j6gen2_v8 + db_j6gen2_v9
- largebus (1,228 frames): db_largebus_v1 + db_largebus_v2 + db_largebus_v3

**Total BEV Center Distance mAP (eval range = 0.0 - 50.0m): 0.8824**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 64,520 | 0.9021 | 0.853 / 0.901 / 0.921 / 0.933 | 0.904 / 0.931 / 0.937 / 0.939 | 0.261 / 0.202 / 0.179 / 0.174 |
| truck | 6,947 | 0.8626 | 0.736 / 0.863 / 0.910 / 0.941 | 0.800 / 0.876 / 0.903 / 0.920 | 0.244 / 0.192 / 0.191 / 0.166 |
| bus | 2,275 | 0.9419 | 0.865 / 0.934 / 0.983 / 0.985 | 0.911 / 0.958 / 0.978 / 0.980 | 0.203 / 0.164 / 0.164 / 0.162 |
| bicycle | 1,379 | 0.8489 | 0.804 / 0.849 / 0.869 / 0.874 | 0.847 / 0.867 / 0.876 / 0.879 | 0.208 / 0.191 / 0.174 / 0.174 |
| pedestrian | 19,421 | 0.8567 | 0.834 / 0.853 / 0.865 / 0.875 | 0.822 / 0.832 / 0.838 / 0.844 | 0.159 / 0.154 / 0.144 / 0.149 |
| **ALL** | 94,542 | 0.8824 | — | — | — |

**Total BEV Center Distance mAP (eval range = 50.0 - 90.0m): 0.7187**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 58,562 | 0.8187 | 0.692 / 0.816 / 0.873 / 0.893 | 0.780 / 0.852 / 0.879 / 0.886 | 0.217 / 0.172 / 0.165 / 0.165 |
| truck | 5,101 | 0.6840 | 0.482 / 0.668 / 0.772 / 0.814 | 0.632 / 0.742 / 0.797 / 0.815 | 0.206 / 0.207 / 0.185 / 0.161 |
| bus | 2,078 | 0.8252 | 0.627 / 0.816 / 0.918 / 0.940 | 0.732 / 0.847 / 0.904 / 0.918 | 0.414 / 0.213 / 0.211 / 0.161 |
| bicycle | 758 | 0.5866 | 0.498 / 0.603 / 0.622 / 0.624 | 0.637 / 0.677 / 0.683 / 0.683 | 0.183 / 0.159 / 0.159 / 0.183 |
| pedestrian | 10,283 | 0.6791 | 0.648 / 0.675 / 0.691 / 0.703 | 0.690 / 0.704 / 0.713 / 0.720 | 0.136 / 0.136 / 0.136 / 0.137 |
| **ALL** | 76,782 | 0.7187 | — | — | — |

**Total BEV Center Distance mAP (eval range = 90.0 - 121.0m): 0.5221**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 20,371 | 0.6798 | 0.489 / 0.673 / 0.763 / 0.795 | 0.636 / 0.736 / 0.781 / 0.794 | 0.196 / 0.160 / 0.153 / 0.151 |
| truck | 3,172 | 0.5176 | 0.228 / 0.453 / 0.653 / 0.738 | 0.446 / 0.600 / 0.715 / 0.762 | 0.208 / 0.206 / 0.162 / 0.140 |
| bus | 376 | 0.5396 | 0.274 / 0.557 / 0.646 / 0.682 | 0.458 / 0.669 / 0.715 / 0.733 | 0.215 / 0.149 / 0.120 / 0.120 |
| bicycle | 155 | 0.4170 | 0.316 / 0.419 / 0.466 / 0.466 | 0.487 / 0.553 / 0.589 / 0.589 | 0.199 / 0.166 / 0.166 / 0.166 |
| pedestrian | 2,794 | 0.4565 | 0.442 / 0.452 / 0.462 / 0.471 | 0.563 / 0.569 / 0.573 / 0.578 | 0.120 / 0.120 / 0.120 / 0.120 |
| **ALL** | 26,868 | 0.5221 | — | — | — |

**Total BEV Center Distance mAP (eval range = 0.0 - 121.0m): 0.7990**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 143,453 | 0.8505 | 0.752 / 0.849 / 0.891 / 0.911 | 0.819 / 0.874 / 0.894 / 0.900 | 0.229 / 0.196 / 0.172 / 0.165 |
| truck | 15,220 | 0.7431 | 0.554 / 0.724 / 0.824 / 0.871 | 0.677 / 0.779 / 0.834 / 0.857 | 0.232 / 0.207 / 0.186 / 0.167 |
| bus | 4,729 | 0.8714 | 0.726 / 0.866 / 0.939 / 0.955 | 0.804 / 0.890 / 0.928 / 0.937 | 0.346 / 0.213 / 0.162 / 0.161 |
| bicycle | 2,292 | 0.7493 | 0.685 / 0.754 / 0.777 / 0.781 | 0.760 / 0.789 / 0.799 / 0.801 | 0.191 / 0.191 / 0.191 / 0.191 |
| pedestrian | 32,498 | 0.7807 | 0.755 / 0.777 / 0.790 / 0.801 | 0.760 / 0.771 / 0.778 / 0.784 | 0.152 / 0.137 / 0.136 / 0.136 |
| **ALL** | 198,192 | 0.7990 | — | — | — |

---

**LargeBus**: db_largebus_v1 + db_largebus_v2 + db_largebus_v3 (1,228 frames)

**Total BEV Center Distance mAP (eval range = 0.0 - 50.0m): 0.8939**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 14,883 | 0.9231 | 0.884 / 0.925 / 0.937 / 0.946 | 0.922 / 0.947 / 0.952 / 0.952 | 0.231 / 0.179 / 0.179 / 0.179 |
| truck | 1,193 | 0.8895 | 0.748 / 0.909 / 0.938 / 0.963 | 0.829 / 0.921 / 0.939 / 0.944 | 0.269 / 0.200 / 0.188 / 0.116 |
| bus | 336 | 0.9514 | 0.855 / 0.983 / 0.984 / 0.984 | 0.895 / 0.960 / 0.963 / 0.963 | 0.419 / 0.173 / 0.173 / 0.173 |
| bicycle | 740 | 0.8273 | 0.754 / 0.824 / 0.862 / 0.869 | 0.824 / 0.854 / 0.866 / 0.872 | 0.250 / 0.246 / 0.198 / 0.198 |
| pedestrian | 5,059 | 0.8783 | 0.862 / 0.876 / 0.883 / 0.891 | 0.849 / 0.857 / 0.862 / 0.866 | 0.150 / 0.150 / 0.148 / 0.135 |
| **ALL** | 22,211 | 0.8939 | — | — | — |

**Total BEV Center Distance mAP (eval range = 50.0 - 90.0m): 0.7679**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 10,994 | 0.8568 | 0.757 / 0.861 / 0.898 / 0.911 | 0.822 / 0.881 / 0.898 / 0.901 | 0.210 / 0.176 / 0.160 / 0.160 |
| truck | 1,011 | 0.7654 | 0.587 / 0.771 / 0.843 / 0.860 | 0.708 / 0.818 / 0.851 / 0.854 | 0.221 / 0.219 / 0.166 / 0.150 |
| bus | 143 | 0.8723 | 0.696 / 0.922 / 0.932 / 0.939 | 0.788 / 0.908 / 0.915 / 0.915 | 0.295 / 0.499 / 0.499 / 0.499 |
| bicycle | 463 | 0.5970 | 0.479 / 0.614 / 0.646 / 0.648 | 0.626 / 0.682 / 0.692 / 0.692 | 0.150 / 0.159 / 0.159 / 0.159 |
| pedestrian | 3,754 | 0.7481 | 0.725 / 0.747 / 0.755 / 0.766 | 0.738 / 0.749 / 0.755 / 0.761 | 0.123 / 0.121 / 0.121 / 0.121 |
| **ALL** | 16,365 | 0.7679 | — | — | — |

**Total BEV Center Distance mAP (eval range = 90.0 - 121.0m): 0.5929**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 3,018 | 0.7246 | 0.572 / 0.729 / 0.790 / 0.807 | 0.689 / 0.766 / 0.792 / 0.801 | 0.228 / 0.228 / 0.155 / 0.160 |
| truck | 602 | 0.6600 | 0.378 / 0.673 / 0.780 / 0.809 | 0.574 / 0.753 / 0.811 / 0.821 | 0.207 / 0.201 / 0.177 / 0.177 |
| bus | 60 | 0.6413 | 0.463 / 0.629 / 0.736 / 0.737 | 0.634 / 0.752 / 0.800 / 0.800 | 0.216 / 0.216 / 0.086 / 0.086 |
| bicycle | 85 | 0.3893 | 0.271 / 0.383 / 0.451 / 0.452 | 0.456 / 0.544 / 0.595 / 0.595 | 0.166 / 0.166 / 0.166 / 0.166 |
| pedestrian | 1,121 | 0.5496 | 0.536 / 0.546 / 0.552 / 0.565 | 0.622 / 0.629 / 0.633 / 0.638 | 0.118 / 0.118 / 0.118 / 0.121 |
| **ALL** | 4,886 | 0.5929 | — | — | — |

**Total BEV Center Distance mAP (eval range = 0.0 - 121.0m): 0.8261**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 28,895 | 0.8885 | 0.814 / 0.891 / 0.919 / 0.930 | 0.863 / 0.905 / 0.916 / 0.919 | 0.231 / 0.182 / 0.179 / 0.176 |
| truck | 2,806 | 0.8045 | 0.619 / 0.816 / 0.880 / 0.903 | 0.733 / 0.850 / 0.882 / 0.887 | 0.233 / 0.199 / 0.186 / 0.169 |
| bus | 539 | 0.8988 | 0.776 / 0.929 / 0.945 / 0.946 | 0.835 / 0.921 / 0.929 / 0.929 | 0.460 / 0.208 / 0.208 / 0.208 |
| bicycle | 1,288 | 0.7338 | 0.640 / 0.737 / 0.776 / 0.782 | 0.731 / 0.773 / 0.792 / 0.796 | 0.185 / 0.185 / 0.162 / 0.162 |
| pedestrian | 9,934 | 0.8051 | 0.786 / 0.803 / 0.811 / 0.821 | 0.781 / 0.791 / 0.796 / 0.801 | 0.150 / 0.135 / 0.135 / 0.135 |
| **ALL** | 43,462 | 0.8261 | — | — | — |

---

**J6Gen2**: db_j6gen2_v1 + db_j6gen2_v2 + db_j6gen2_v3 + db_j6gen2_v4 + db_j6gen2_v5 + db_j6gen2_v6 + db_j6gen2_v7 + db_j6gen2_v8 + db_j6gen2_v9 (3,951 frames)

**Total BEV Center Distance mAP (eval range = 0.0 - 50.0m): 0.8833**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 49,637 | 0.8941 | 0.842 / 0.891 / 0.912 / 0.931 | 0.899 / 0.926 / 0.933 / 0.935 | 0.272 / 0.203 / 0.188 / 0.173 |
| truck | 5,754 | 0.8571 | 0.733 / 0.855 / 0.904 / 0.936 | 0.795 / 0.867 / 0.895 / 0.915 | 0.242 / 0.191 / 0.191 / 0.180 |
| bus | 1,939 | 0.9386 | 0.864 / 0.931 / 0.975 / 0.985 | 0.916 / 0.957 / 0.981 / 0.984 | 0.265 / 0.187 / 0.139 / 0.138 |
| bicycle | 639 | 0.8776 | 0.867 / 0.881 / 0.881 / 0.881 | 0.879 / 0.887 / 0.887 / 0.887 | 0.174 / 0.174 / 0.174 / 0.174 |
| pedestrian | 14,362 | 0.8492 | 0.824 / 0.846 / 0.858 / 0.869 | 0.813 / 0.825 / 0.831 / 0.837 | 0.162 / 0.160 / 0.155 / 0.159 |
| **ALL** | 72,331 | 0.8833 | — | — | — |

**Total BEV Center Distance mAP (eval range = 50.0 - 90.0m): 0.7035**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 47,568 | 0.8111 | 0.678 / 0.809 / 0.868 / 0.890 | 0.771 / 0.846 / 0.874 / 0.882 | 0.243 / 0.170 / 0.165 / 0.165 |
| truck | 4,090 | 0.6651 | 0.459 / 0.644 / 0.755 / 0.803 | 0.613 / 0.724 / 0.785 / 0.806 | 0.206 / 0.206 / 0.185 / 0.164 |
| bus | 1,935 | 0.8227 | 0.622 / 0.807 / 0.919 / 0.943 | 0.729 / 0.843 / 0.904 / 0.920 | 0.413 / 0.212 / 0.176 / 0.161 |
| bicycle | 295 | 0.5784 | 0.543 / 0.588 / 0.590 / 0.592 | 0.675 / 0.686 / 0.686 / 0.690 | 0.215 / 0.207 / 0.207 / 0.207 |
| pedestrian | 6,529 | 0.6402 | 0.605 / 0.635 / 0.654 / 0.667 | 0.665 / 0.681 / 0.692 / 0.699 | 0.136 / 0.136 / 0.136 / 0.136 |
| **ALL** | 60,417 | 0.7035 | — | — | — |

**Total BEV Center Distance mAP (eval range = 90.0 - 121.0m): 0.5020**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 17,353 | 0.6719 | 0.474 / 0.662 / 0.758 / 0.793 | 0.628 / 0.732 / 0.779 / 0.793 | 0.188 / 0.171 / 0.146 / 0.150 |
| truck | 2,570 | 0.4839 | 0.193 / 0.399 / 0.622 / 0.722 | 0.414 / 0.561 / 0.692 / 0.750 | 0.206 / 0.206 / 0.161 / 0.128 |
| bus | 316 | 0.5176 | 0.234 / 0.541 / 0.626 / 0.669 | 0.429 / 0.656 / 0.703 / 0.724 | 0.306 / 0.120 / 0.120 / 0.120 |
| bicycle | 70 | 0.4435 | 0.340 / 0.466 / 0.484 / 0.484 | 0.513 / 0.584 / 0.602 / 0.602 | 0.199 / 0.199 / 0.199 / 0.199 |
| pedestrian | 1,673 | 0.3932 | 0.378 / 0.388 / 0.400 / 0.407 | 0.522 / 0.527 / 0.531 / 0.535 | 0.136 / 0.136 / 0.125 / 0.136 |
| **ALL** | 21,982 | 0.5020 | — | — | — |

**Total BEV Center Distance mAP (eval range = 0.0 - 121.0m): 0.7958**

| class_name | GTs | mAP | AP@0.5/1.0/2.0/4.0 | max_f1@0.5/1.0/2.0/4.0 | optimal_conf@0.5/1.0/2.0/4.0 |
| :---- | ---: | ---: | :---- | :---- | :---- |
| car | 114,558 | 0.8404 | 0.736 / 0.837 / 0.882 / 0.906 | 0.807 / 0.866 / 0.888 / 0.895 | 0.235 / 0.188 / 0.170 / 0.165 |
| truck | 12,414 | 0.7292 | 0.540 / 0.704 / 0.811 / 0.863 | 0.664 / 0.763 / 0.823 / 0.851 | 0.248 / 0.207 / 0.180 / 0.164 |
| bus | 4,190 | 0.8680 | 0.719 / 0.857 / 0.940 / 0.956 | 0.801 / 0.886 / 0.928 / 0.939 | 0.344 / 0.212 / 0.176 / 0.161 |
| bicycle | 1,004 | 0.7709 | 0.746 / 0.778 / 0.780 / 0.780 | 0.800 / 0.813 / 0.814 / 0.815 | 0.191 / 0.191 / 0.191 / 0.191 |
| pedestrian | 22,564 | 0.7703 | 0.742 / 0.766 / 0.781 / 0.792 | 0.751 / 0.763 / 0.771 / 0.777 | 0.152 / 0.138 / 0.138 / 0.144 |
| **ALL** | 154,730 | 0.7958 | — | — | — |

</details>

### BEVFusion-LiDAR J6Gen2_base/2.7.1

<details>
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