Unverified Commit 6b1602f1 authored by ChaimZhu's avatar ChaimZhu Committed by GitHub
Browse files

[Feature] Add SMOKE benchmark (#988)

* add metafile and readme

* fix typos

* refine some typos

* fix some typos

* add smoke in readme and model-zoo

* change dlanet to dla

* change dlanet to dla in metafile
parent 36f658a5
......@@ -84,6 +84,7 @@ Support backbones:
- [x] PointNet++ (NeurIPS'2017)
- [x] RegNet (CVPR'2020)
- [x] DGCNN (TOG'2019)
- [x] DLA (CVPR'2018)
Support methods
......@@ -104,26 +105,28 @@ Support methods
- [x] [ImVoxelNet (Arxiv'2021)](configs/imvoxelnet/README.md)
- [x] [PAConv (CVPR'2021)](configs/paconv/README.md)
- [x] [DGCNN (TOG'2019)](configs/dgcnn/README.md)
| | ResNet | ResNeXt | SENet |PointNet++ |DGCNN | HRNet | RegNetX | Res2Net |
|--------------------|:--------:|:--------:|:--------:|:---------:|:---------:|:-----:|:--------:|:-----:|
| SECOND | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| PointPillars | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| FreeAnchor | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| VoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| H3DNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| 3DSSD | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| Part-A2 | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| MVXNet | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| CenterPoint | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| SSN | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| ImVoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| FCOS3D | ✓ | ☐ | ☐ | ✗ | ✗ | ☐ | ☐ | ☐ |
| PointNet++ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| Group-Free-3D | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| ImVoxelNet | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PAConv | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| DGCNN | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
- [x] [SMOKE (CVPRW'2020)](configs/smoke/README.md)
| | ResNet | ResNeXt | SENet |PointNet++ |DGCNN | HRNet | RegNetX | Res2Net | DLA |
|--------------------|:--------:|:--------:|:--------:|:---------:|:---------:|:-----:|:--------:|:-----:|:---:|
| SECOND | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| PointPillars | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| FreeAnchor | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| VoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| H3DNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| 3DSSD | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| Part-A2 | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| MVXNet | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| CenterPoint | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| SSN | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| ImVoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| FCOS3D | ✓ | ☐ | ☐ | ✗ | ✗ | ☐ | ☐ | ☐ | ✗
| PointNet++ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| Group-Free-3D | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| ImVoxelNet | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗
| PAConv | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| DGCNN | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗
| SMOKE | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓
Other features
- [x] [Dynamic Voxelization](configs/dynamic_voxelization/README.md)
......
......@@ -83,6 +83,7 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱, 下一代
- [x] PointNet++ (NeurIPS'2017)
- [x] RegNet (CVPR'2020)
- [x] DGCNN (TOG'2019)
- [x] DLA (CVPR'2018)
已支持的算法:
......@@ -103,26 +104,28 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱, 下一代
- [x] [ImVoxelNet (Arxiv'2021)](configs/imvoxelnet/README.md)
- [x] [PAConv (CVPR'2021)](configs/paconv/README.md)
- [x] [DGCNN (TOG'2019)](configs/dgcnn/README.md)
| | ResNet | ResNeXt | SENet |PointNet++ |DGCNN | HRNet | RegNetX | Res2Net |
|--------------------|:--------:|:--------:|:--------:|:---------:|:---------:|:-----:|:--------:|:-----:|
| SECOND | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| PointPillars | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| FreeAnchor | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| VoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| H3DNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| 3DSSD | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| Part-A2 | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| MVXNet | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| CenterPoint | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| SSN | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ |
| ImVoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| FCOS3D | ✓ | ☐ | ☐ | ✗ | ✗ | ☐ | ☐ | ☐ |
| PointNet++ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| Group-Free-3D | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| ImVoxelNet | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| PAConv | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ |
| DGCNN | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
- [x] [SMOKE (CVPRW'2020)](configs/smoke/README.md)
| | ResNet | ResNeXt | SENet |PointNet++ |DGCNN | HRNet | RegNetX | Res2Net | DLA |
|--------------------|:--------:|:--------:|:--------:|:---------:|:---------:|:-----:|:--------:|:-----:|:---:|
| SECOND | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| PointPillars | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| FreeAnchor | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| VoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| H3DNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| 3DSSD | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| Part-A2 | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| MVXNet | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| CenterPoint | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| SSN | ☐ | ☐ | ☐ | ✗ | ✗ | ☐ | ✓ | ☐ | ✗
| ImVoteNet | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| FCOS3D | ✓ | ☐ | ☐ | ✗ | ✗ | ☐ | ☐ | ☐ | ✗
| PointNet++ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| Group-Free-3D | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| ImVoxelNet | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗
| PAConv | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗
| DGCNN | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✗
| SMOKE | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓
其他特性
- [x] [Dynamic Voxelization](configs/dynamic_voxelization/README.md)
......
# SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
## Introduction
<!-- [ALGORITHM] -->
We implement SMOKE and provide the results and checkpoints on KITTI dataset.
```
@inproceedings{liu2020smoke,
title={Smoke: Single-stage monocular 3d object detection via keypoint estimation},
author={Liu, Zechen and Wu, Zizhang and T{\'o}th, Roland},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
pages={996--997},
year={2020}
}
```
## Results
### KITTI
| Backbone | Lr schd | Mem (GB) | Inf time (fps) | mAP | Download |
| :---------: | :-----: | :------: | :------------: | :----: | :------: |
|[DLA34](./smoke_dla34_pytorch_dlaneck_gn-head_kitti_mono3d.py)|6x|9.64||13.85|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/smoke/smoke_dla34_pytorch_dlaneck_gn-all_8x4_6x_kitti-mono3d_20210929_015553-d46d9bb0.pth) &#124; [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/smoke/smoke_dla34_pytorch_dlaneck_gn-all_8x4_6x_kitti-mono3d_20210929_015553.log.json)
Note: mAP represents Car moderate 3D strict AP11 results.
Detailed performance on KITTI 3D detection (3D/BEV) is as follows, evaluated by AP11 metric:
| | Easy | Moderate | Hard |
|-------------|:-------------:|:--------------:|:------------:|
| Car | 16.92 / 22.97 | 13.85 / 18.32 | 11.90 / 15.88|
| Pedestrian | 11.13 / 12.61| 11.10 / 11.32 | 10.67 / 11.14|
| Cyclist | 0.99 / 1.47 | 0.54 / 0.65 | 0.55 / 0.67 |
Collections:
- Name: SMOKE
Metadata:
Training Data: KITTI
Training Techniques:
- Adam
Training Resources: 4x V100 GPUS
Architecture:
- SMOKEMono3DHead
- DLA
Paper:
URL: https://arxiv.org/abs/2002.10111
Title: 'SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation'
README: configs/smoke/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection3d/blob/master/mmdet3d/models/detectors/smoke_mono3d.py#L7
Version: v0.17.1
Models:
- Name: smoke_dla34_pytorch_dlaneck_gn-all_8x4_6x_kitti-mono3d
In Collection: SMOKE
Config: configs/smoke/smoke_dla34_pytorch_dlaneck_gn-all_8x4_6x_kitti-mono3d.py
Metadata:
Training Memory (GB): 9.6
Results:
- Task: 3D Object Detection
Dataset: KITTI
Metrics:
mAP: 13.8
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/smoke/smoke_dla34_pytorch_dlaneck_gn-all_8x4_6x_kitti-mono3d_20210929_015553-d46d9bb0.pth
......@@ -80,4 +80,8 @@ Please refer to [PAConv](https://github.com/open-mmlab/mmdetection3d/blob/master
### DGCNN
Please refer to [DGCNN](https://github.com/open-mmlab/mmdetection3d/blob/master/configs/dgcnn) for details. We provide DGCNN baselines on S3DIS dataset.
Please refer to [DGCNN](https://github.com/open-mmlab/mmdetection3d/tree/v1.0.0.dev0/configs/dgcnn) for details. We provide DGCNN baselines on S3DIS dataset.
### SMOKE
Please refer to [SMOKE](https://github.com/open-mmlab/mmdetection3d/tree/v1.0.0.dev0/configs/smoke) for details. We provide SMOKE baselines on KITTI dataset.
......@@ -82,4 +82,8 @@
### DGCNN
请参考 [DGCNN](https://github.com/open-mmlab/mmdetection3d/blob/master/configs/dgcnn) 获取更多细节,我们在 S3DIS 数据集上给出了相应的结果.
请参考 [DGCNN](https://github.com/open-mmlab/mmdetection3d/tree/v1.0.0.dev0/configs/dgcnn) 获取更多细节,我们在 S3DIS 数据集上给出了相应的结果.
### SMOKE
请考考 [SMOKE](https://github.com/open-mmlab/mmdetection3d/tree/v1.0.0.dev0/configs/smoke) 获取更多细节,我们在 KITTI 数据集上给出了相应的结果.
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment