Awesome
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<h1> BEVDistill </h1>
<h3>Cross-Modal BEV Distillation for Multi-View 3D Object Detection</h3>
<br>Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang, Qinhong Jiang, Feng Zhao.
<br>
<div><a href="https://arxiv.org/pdf/2211.09386.pdf">[Paper] </a></div>
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<img src='figs/framework.png'>
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NOTE
This code is an initial release with BEVFormer-T only, we will release a full version in the future.
Run
# baseline
./tools/dist_train.sh projects/configs/video_bevformer/bevformer_128x128_r50_2x.py 8
# BEVDistill
./tools/dist_train_distill.sh projects/configs/bevdistill/bevdistill_r50_128x128_900query_bboxrweighttop100_bevgt_mocov2_merge_r1_2x.py 8
Performance
nuScenes Val set
| Model | config | mAP | NDS |
|---|
| BEVFormer-R50 | | 35.2 | 42.3 |
| BEVDistill-R50 | | 38.6 | 45.7 |
| BEVFormer-T-R50 | link | 38.3 | 48.8 |
| BEVDistill-T-R50 | link | 40.7 | 51.5 |
| BEVFormer-T-R101 | link | 40.5 | 50.6 |
| BEVDistill-T-R101 | link | 41.7 | 52.4 |
Pretrain Checkpoints
| Model | Weight | mAP | NDS |
|---|
| ObjectDGCNN (Teacher) | link | 67.4 | 61.5 |
| FCOS3D r50 (Student) | link | | |