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[ECCV2022, IJCAI2022] AutoAlignV2: Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object Detection

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AutoAlignV2

Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object Detection


Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang, Qinhong Jiang, Feng Zhao.

Performance

nuScenes Val set

Model config mAP NDS
Baseline 1/8 subset - -
AutoAlignV2 1/8 subset 58.5 63.2

nuScenes Test Leaderboard

Model mAP NDS
AutoAlign 65.8 70.9
AutoAlignV2 68.4 72.4

Note

The code is released without rechecking. We will clean up and recheck the code recently.

Get Started

Install Deformable Ops from DeformDETR

cd ops
sh ./make.sh
# unit test (should see all checking is True)
python test.py

Prepare Dataset

python tools/create_data.py nuscenes --root-path ./data/nuscenes --out-dir ./data/nuscenes --extra-tag nuscenes --version v1.0

Train Model

./tools/dist_train.sh aav2_cfg/centerpoint_voxel_nus_8subset_bs4_img1_nuimg_detach_deform_multipts.py 8

Test Model

./tools/dist_test.sh aav2_cfg/centerpoint_voxel_nus_8subset_bs4_img1_nuimg_detach_deform_multipts.py work_dirs/centerpoint_voxel_nus_8subset_bs4_img1_nuimg_detach_deform_multipts/epoch_20.pth 8 --eval bbox

Pretrained Model Weights

Model Weights
Pretrained YOLOX-640 https://drive.google.com/file/d/1DuA16ocF8Dmfl0nC3NNSKG_Yqq-aXuLH/view?usp=sharing
Pretrained YOLOX-800 https://drive.google.com/file/d/1YPSjG38qXrV8gYlq5FuhQCjfRIUvhaju/view?usp=sharing
AutoAlignV2 1/8 subset https://drive.google.com/file/d/1F_B4bq5Y6QdkUHQbqeLaEGl-IZHHe1WB/view?usp=sharing

Citation

If you find our work useful for your research, please consider citing the paper

@article{chen2022autoalignv2,
  title={AutoAlignV2: Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object Detection},
  author={Chen, Zehui and Li, Zhenyu and Zhang, Shiquan and Fang, Liangji and Jiang, Qinhong and Zhao, Feng},
  journal={ECCV},
  year={2022}
}

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[ECCV2022, IJCAI2022] AutoAlignV2: Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object Detection

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