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Unverified Commit f40d8d28 authored by ZhuLifa's avatar ZhuLifa Committed by GitHub
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[Docs] Add 6 models in benchmark & model zoo in README.md (#2600) 

* [Docs]: Add BEVFusion in benchmark & model zoo in README

* [Docs]: Add CenterFormer in benchmark & model zoo in README

* [Docs]: Add TR3D in benchmark & model zoo in README

* [Docs]: Add DETR3D and PETR in benchmark & model zoo in README

* [Docs]: Add TPVFormer in benchmark & model zoo in README

* [Docs]: Add 6 models in benchmark & model zoo in README_zh-CN

* [Docs]: Add 6 models in model_zoo.md

* [Style]: Stylize the code
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README.md
View file @ f40d8d28
...@@ -162,10 +162,10 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md). ...@@ -162,10 +162,10 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md).
<tbody> <tbody>
<tr align="center" valign="middle"> <tr align="center" valign="middle">
<td> <td>
<b>3D Object Detection</b> <b>LiDAR-based 3D Object Detection</b>
</td> </td>
<td> <td>
<b>Monocular 3D Object Detection</b> <b>Camera-based 3D Object Detection</b>
</td> </td>
<td> <td>
<b>Multi-modal 3D Object Detection</b> <b>Multi-modal 3D Object Detection</b>
...@@ -187,6 +187,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md). ...@@ -187,6 +187,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md).
<li><a href="configs/parta2">Part-A2 (TPAMI'2020)</a></li> <li><a href="configs/parta2">Part-A2 (TPAMI'2020)</a></li>
<li><a href="configs/centerpoint">CenterPoint (CVPR'2021)</a></li> <li><a href="configs/centerpoint">CenterPoint (CVPR'2021)</a></li>
<li><a href="configs/pv_rcnn">PV-RCNN (CVPR'2020)</a></li> <li><a href="configs/pv_rcnn">PV-RCNN (CVPR'2020)</a></li>
<li><a href="projects/CenterFormer">CenterFormer (ECCV'2022)</a></li>
</ul> </ul>
<li><b>Indoor</b></li> <li><b>Indoor</b></li>
<ul> <ul>
...@@ -194,6 +195,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md). ...@@ -194,6 +195,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md).
<li><a href="configs/h3dnet">H3DNet (ECCV'2020)</a></li> <li><a href="configs/h3dnet">H3DNet (ECCV'2020)</a></li>
<li><a href="configs/groupfree3d">Group-Free-3D (ICCV'2021)</a></li> <li><a href="configs/groupfree3d">Group-Free-3D (ICCV'2021)</a></li>
<li><a href="configs/fcaf3d">FCAF3D (ECCV'2022)</a></li> <li><a href="configs/fcaf3d">FCAF3D (ECCV'2022)</a></li>
<li><a href="projects/TR3D">TR3D (ArXiv'2023)</a></li>
</ul> </ul>
</td> </td>
<td> <td>
...@@ -204,6 +206,8 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md). ...@@ -204,6 +206,8 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md).
<li><a href="configs/fcos3d">FCOS3D (ICCVW'2021)</a></li> <li><a href="configs/fcos3d">FCOS3D (ICCVW'2021)</a></li>
<li><a href="configs/pgd">PGD (CoRL'2021)</a></li> <li><a href="configs/pgd">PGD (CoRL'2021)</a></li>
<li><a href="configs/monoflex">MonoFlex (CVPR'2021)</a></li> <li><a href="configs/monoflex">MonoFlex (CVPR'2021)</a></li>
<li><a href="projects/DETR3D">DETR3D (CoRL'2021)</a></li>
<li><a href="projects/PETR">PETR (ECCV'2022)</a></li>
</ul> </ul>
<li><b>Indoor</b></li> <li><b>Indoor</b></li>
<ul> <ul>
...@@ -214,6 +218,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md). ...@@ -214,6 +218,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md).
<li><b>Outdoor</b></li> <li><b>Outdoor</b></li>
<ul> <ul>
<li><a href="configs/mvxnet">MVXNet (ICRA'2019)</a></li> <li><a href="configs/mvxnet">MVXNet (ICRA'2019)</a></li>
<li><a href="projects/BEVFusion">BEVFusion (ICRA'2023)</a></li>
</ul> </ul>
<li><b>Indoor</b></li> <li><b>Indoor</b></li>
<ul> <ul>
...@@ -226,6 +231,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md). ...@@ -226,6 +231,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md).
<li><a href="configs/minkunet">MinkUNet (CVPR'2019)</a></li> <li><a href="configs/minkunet">MinkUNet (CVPR'2019)</a></li>
<li><a href="configs/spvcnn">SPVCNN (ECCV'2020)</a></li> <li><a href="configs/spvcnn">SPVCNN (ECCV'2020)</a></li>
<li><a href="configs/cylinder3d">Cylinder3D (CVPR'2021)</a></li> <li><a href="configs/cylinder3d">Cylinder3D (CVPR'2021)</a></li>
<li><a href="projects/TPVFormer">TPVFormer (CVPR'2023)</a></li>
</ul> </ul>
<li><b>Indoor</b></li> <li><b>Indoor</b></li>
<ul> <ul>
...@@ -241,34 +247,40 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md). ...@@ -241,34 +247,40 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md).
</tbody> </tbody>
</table> </table>
| | ResNet | PointNet++ | SECOND | DGCNN | RegNetX | DLA | MinkResNet | Cylinder3D | MinkUNet | | | ResNet | VoVNet | Swin-T | PointNet++ | SECOND | DGCNN | RegNetX | DLA | MinkResNet | Cylinder3D | MinkUNet |
| :-----------: | :----: | :--------: | :----: | :---: | :-----: | :-: | :--------: | :--------: | :------: | | :-----------: | :----: | :----: | :----: | :--------: | :----: | :---: | :-----: | :-: | :--------: | :--------: | :------: |
| SECOND | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | SECOND | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PointPillars | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | | PointPillars | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| FreeAnchor | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | | FreeAnchor | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| VoteNet | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | VoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| H3DNet | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | H3DNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| 3DSSD | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | 3DSSD | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Part-A2 | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | Part-A2 | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| MVXNet | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | MVXNet | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| CenterPoint | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | CenterPoint | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| SSN | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | | SSN | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| ImVoteNet | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | ImVoteNet | ✓ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| FCOS3D | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | FCOS3D | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PointNet++ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | PointNet++ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Group-Free-3D | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | Group-Free-3D | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| ImVoxelNet | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | ImVoxelNet | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PAConv | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | PAConv | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| DGCNN | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | | DGCNN | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ |
| SMOKE | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | | SMOKE | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
| PGD | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | PGD | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| MonoFlex | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | | MonoFlex | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
| SA-SSD | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | SA-SSD | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| FCAF3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | | FCAF3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
| PV-RCNN | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | PV-RCNN | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Cylinder3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | | Cylinder3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| MinkUNet | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | | MinkUNet | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ |
| SPVCNN | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | | SPVCNN | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ |
| BEVFusion | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| CenterFormer | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| TR3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
| DETR3D | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PETR | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| TPVFormer | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
**Note:** All the about **300+ models, methods of 40+ papers** in 2D detection supported by [MMDetection](https://github.com/open-mmlab/mmdetection/blob/3.x/docs/en/model_zoo.md) can be trained or used in this codebase. **Note:** All the about **300+ models, methods of 40+ papers** in 2D detection supported by [MMDetection](https://github.com/open-mmlab/mmdetection/blob/3.x/docs/en/model_zoo.md) can be trained or used in this codebase.
......
README_zh-CN.md
View file @ f40d8d28
...@@ -158,10 +158,10 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代 ...@@ -158,10 +158,10 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代
<tbody> <tbody>
<tr align="center" valign="middle"> <tr align="center" valign="middle">
<td> <td>
<b>3D 目标检测</b> <b>激光雷达 3D 目标检测</b>
</td> </td>
<td> <td>
<b>单目 3D 目标检测</b> <b>相机 3D 目标检测</b>
</td> </td>
<td> <td>
<b>多模态 3D 目标检测</b> <b>多模态 3D 目标检测</b>
...@@ -182,6 +182,8 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代 ...@@ -182,6 +182,8 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代
<li><a href="configs/point_rcnn">PointRCNN (CVPR'2019)</a></li> <li><a href="configs/point_rcnn">PointRCNN (CVPR'2019)</a></li>
<li><a href="configs/parta2">Part-A2 (TPAMI'2020)</a></li> <li><a href="configs/parta2">Part-A2 (TPAMI'2020)</a></li>
<li><a href="configs/centerpoint">CenterPoint (CVPR'2021)</a></li> <li><a href="configs/centerpoint">CenterPoint (CVPR'2021)</a></li>
<li><a href="configs/pv_rcnn">PV-RCNN (CVPR'2020)</a></li>
<li><a href="projects/CenterFormer">CenterFormer (ECCV'2022)</a></li>
</ul> </ul>
<li><b>室内</b></li> <li><b>室内</b></li>
<ul> <ul>
...@@ -189,6 +191,7 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代 ...@@ -189,6 +191,7 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代
<li><a href="configs/h3dnet">H3DNet (ECCV'2020)</a></li> <li><a href="configs/h3dnet">H3DNet (ECCV'2020)</a></li>
<li><a href="configs/groupfree3d">Group-Free-3D (ICCV'2021)</a></li> <li><a href="configs/groupfree3d">Group-Free-3D (ICCV'2021)</a></li>
<li><a href="configs/fcaf3d">FCAF3D (ECCV'2022)</a></li> <li><a href="configs/fcaf3d">FCAF3D (ECCV'2022)</a></li>
<li><a href="projects/TR3D">TR3D (ArXiv'2023)</a></li>
</ul> </ul>
</td> </td>
<td> <td>
...@@ -199,6 +202,8 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代 ...@@ -199,6 +202,8 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代
<li><a href="configs/fcos3d">FCOS3D (ICCVW'2021)</a></li> <li><a href="configs/fcos3d">FCOS3D (ICCVW'2021)</a></li>
<li><a href="configs/pgd">PGD (CoRL'2021)</a></li> <li><a href="configs/pgd">PGD (CoRL'2021)</a></li>
<li><a href="configs/monoflex">MonoFlex (CVPR'2021)</a></li> <li><a href="configs/monoflex">MonoFlex (CVPR'2021)</a></li>
<li><a href="projects/DETR3D">DETR3D (CoRL'2021)</a></li>
<li><a href="projects/PETR">PETR (ECCV'2022)</a></li>
</ul> </ul>
<li><b>Indoor</b></li> <li><b>Indoor</b></li>
<ul> <ul>
...@@ -209,6 +214,7 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代 ...@@ -209,6 +214,7 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代
<li><b>室外</b></li> <li><b>室外</b></li>
<ul> <ul>
<li><a href="configs/mvxnet">MVXNet (ICRA'2019)</a></li> <li><a href="configs/mvxnet">MVXNet (ICRA'2019)</a></li>
<li><a href="projects/BEVFusion">BEVFusion (ICRA'2023)</a></li>
</ul> </ul>
<li><b>室内</b></li> <li><b>室内</b></li>
<ul> <ul>
...@@ -221,6 +227,7 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代 ...@@ -221,6 +227,7 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代
<li><a href="configs/minkunet">MinkUNet (CVPR'2019)</a></li> <li><a href="configs/minkunet">MinkUNet (CVPR'2019)</a></li>
<li><a href="configs/spvcnn">SPVCNN (ECCV'2020)</a></li> <li><a href="configs/spvcnn">SPVCNN (ECCV'2020)</a></li>
<li><a href="configs/cylinder3d">Cylinder3D (CVPR'2021)</a></li> <li><a href="configs/cylinder3d">Cylinder3D (CVPR'2021)</a></li>
<li><a href="projects/TPVFormer">TPVFormer (CVPR'2023)</a></li>
</ul> </ul>
<li><b>室内</b></li> <li><b>室内</b></li>
<ul> <ul>
...@@ -236,34 +243,40 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代 ...@@ -236,34 +243,40 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱，下一代
</tbody> </tbody>
</table> </table>
| | ResNet | PointNet++ | SECOND | DGCNN | RegNetX | DLA | MinkResNet | Cylinder3D | MinkUNet | | | ResNet | VoVNet | Swin-T | PointNet++ | SECOND | DGCNN | RegNetX | DLA | MinkResNet | Cylinder3D | MinkUNet |
| :-----------: | :----: | :--------: | :----: | :---: | :-----: | :-: | :--------: | :--------: | :------: | | :-----------: | :----: | :----: | :----: | :--------: | :----: | :---: | :-----: | :-: | :--------: | :--------: | :------: |
| SECOND | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | SECOND | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PointPillars | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | | PointPillars | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| FreeAnchor | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | | FreeAnchor | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| VoteNet | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | VoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| H3DNet | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | H3DNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| 3DSSD | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | 3DSSD | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Part-A2 | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | Part-A2 | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| MVXNet | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | MVXNet | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| CenterPoint | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | CenterPoint | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| SSN | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | | SSN | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| ImVoteNet | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | ImVoteNet | ✓ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| FCOS3D | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | FCOS3D | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PointNet++ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | PointNet++ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Group-Free-3D | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | Group-Free-3D | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| ImVoxelNet | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | ImVoxelNet | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PAConv | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | PAConv | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| DGCNN | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | | DGCNN | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ |
| SMOKE | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | | SMOKE | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
| PGD | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | PGD | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| MonoFlex | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | | MonoFlex | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
| SA-SSD | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | SA-SSD | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| FCAF3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | | FCAF3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
| PV-RCNN | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | | PV-RCNN | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Cylinder3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | | Cylinder3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| MinkUNet | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | | MinkUNet | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ |
| SPVCNN | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | | SPVCNN | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ |
| BEVFusion | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| CenterFormer | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| TR3D | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ |
| DETR3D | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PETR | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| TPVFormer | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
**注意：**[MMDetection](https://github.com/open-mmlab/mmdetection/blob/3.x/docs/zh_cn/model_zoo.md) 支持的基于 2D 检测的 **300+ 个模型，40+ 的论文算法**在 MMDetection3D 中都可以被训练或使用。 **注意：**[MMDetection](https://github.com/open-mmlab/mmdetection/blob/3.x/docs/zh_cn/model_zoo.md) 支持的基于 2D 检测的 **300+ 个模型，40+ 的论文算法**在 MMDetection3D 中都可以被训练或使用。
......
docs/en/model_zoo.md
View file @ f40d8d28
...@@ -112,6 +112,30 @@ Please refer to [FCAF3D](https://github.com/open-mmlab/mmdetection3d/blob/main/c ...@@ -112,6 +112,30 @@ Please refer to [FCAF3D](https://github.com/open-mmlab/mmdetection3d/blob/main/c
Please refer to [PV-RCNN](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/configs/pv_rcnn) for details. We provide PV-RCNN baselines on the KITTI dataset. Please refer to [PV-RCNN](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/configs/pv_rcnn) for details. We provide PV-RCNN baselines on the KITTI dataset.
### BEVFusion
Please refer to [BEVFusion](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/BEVFusion) for details. We provide BEVFusion baselines on the NuScenes dataset.
### CenterFormer
Please refer to [CenterFormer](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/CenterFormer) for details. We provide CenterFormer baselines on the Waymo dataset.
### TR3D
Please refer to [TR3D](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/TR3D) for details. We provide TR3D baselines on the ScanNet, SUN RGB-D and S3DIS dataset.
### DETR3D
Please refer to [DETR3D](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/DETR3D) for details. We provide DETR3D baselines on the nuScenes dataset.
### PETR
Please refer to [PETR](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/PETR) for details. We provide PETR baselines on the nuScenes dataset.
### TPVFormer
Please refer to [TPVFormer](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/TPVFormer) for details. We provide TPVFormer baselines on the nuScenes dataset.
### Mixed Precision (FP16) Training ### Mixed Precision (FP16) Training
Please refer to [Mixed Precision (FP16) Training on PointPillars](https://github.com/open-mmlab/mmdetection3d/tree/v1.0.0.dev0/configs/pointpillars/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d.py) for details. Please refer to [Mixed Precision (FP16) Training on PointPillars](https://github.com/open-mmlab/mmdetection3d/tree/v1.0.0.dev0/configs/pointpillars/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d.py) for details.
docs/zh_cn/model_zoo.md
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...@@ -108,6 +108,34 @@ ...@@ -108,6 +108,34 @@
请参考 [FCAF3D](https://github.com/open-mmlab/mmdetection3d/blob/main/configs/fcaf3d) 获取更多的细节，我们在 ScanNet, S3DIS 和 SUN RGB-D 数据集上给出了相应的基准结果。 请参考 [FCAF3D](https://github.com/open-mmlab/mmdetection3d/blob/main/configs/fcaf3d) 获取更多的细节，我们在 ScanNet, S3DIS 和 SUN RGB-D 数据集上给出了相应的基准结果。
### PV-RCNN
请参考 [PV-RCNN](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/configs/pv_rcnn) 获取更多的细节，我们在 KITTI 数据集上给出了相应的基准结果。
### BEVFusion
请参考 [BEVFusion](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/BEVFusion) 获取更多的细节, 我们在 NuScenes 数据集上给出了相应的基准结果。
### CenterFormer
请参考 [CenterFormer](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/CenterFormer) 获取更多的细节, 我们在 Waymo 数据集上给出了相应的基准结果。
### TR3D
请参考 [TR3D](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/TR3D) 获取更多的细节, 我们在 ScanNet, SUN RGB-D 和 S3DIS 数据集上给出了相应的基准结果。
### DETR3D
请参考 [DETR3D](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/DETR3D) 获取更多的细节, 我们在 NuScenes 数据集上给出了相应的基准结果。
### PETR
请参考 [PETR](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/PETR) 获取更多的细节, 我们在 NuScenes 数据集上给出了相应的基准结果。
### TPVFormer
请参考 [TPVFormer](https://github.com/open-mmlab/mmdetection3d/blob/dev-1.x/projects/TPVFormer) 获取更多的细节, 我们在 NuScenes 数据集上给出了相应的基准结果。
### Mixed Precision (FP16) Training ### Mixed Precision (FP16) Training
细节请参考 [Mixed Precision (FP16) Training 在 PointPillars 训练的样例](https://github.com/open-mmlab/mmdetection3d/blob/main/configs/pointpillars/pointpillars_hv_fpn_sbn-all_8xb2-amp-2x_nus-3d.py)。 细节请参考 [Mixed Precision (FP16) Training 在 PointPillars 训练的样例](https://github.com/open-mmlab/mmdetection3d/blob/main/configs/pointpillars/pointpillars_hv_fpn_sbn-all_8xb2-amp-2x_nus-3d.py)。
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