Collections: - Name: RegNetX Metadata: Training Techniques: - AdamW Training Resources: 8x V100 GPUs Architecture: - Faster R-CNN - Hard Voxelization Paper: https://arxiv.org/abs/2003.13678 README: configs/regnet/README.md Models: - Name: hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d In Collection: RegNetX Config: configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d.py Metadata: Training Data: nuScenes Training Memory (GB): 16.4 Results: - Task: 3D Object Detection Dataset: nuScenes Metrics: mAP: 41.2 NDS: 55.2 Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d_20200620_230334-53044f32.pth - Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d In Collection: RegNetX Config: configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py Metadata: Training Data: nuScenes Training Memory (GB): 17.3 Results: - Task: 3D Object Detection Dataset: nuScenes Metrics: mAP: 44.8 NDS: 56.4 Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d_20200620_230239-c694dce7.pth - Name: hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d In Collection: RegNetX Config: configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py Metadata: Training Data: nuScenes Training Memory (GB): 24.0 Results: - Task: 3D Object Detection Dataset: nuScenes Metrics: mAP: 48.2 NDS: 59.3 Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d_20200629_050311-dcd4e090.pth - Name: hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_lyft-3d In Collection: RegNetX Config: configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_lyft-3d.py Metadata: Training Data: Lyft Results: - Task: 3D Object Detection Dataset: Lyft - Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_lyft-3d In Collection: RegNetX Config: configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_lyft-3d.py Metadata: Training Data: Lyft Results: - Task: 3D Object Detection Dataset: Lyft Metrics: Private Score: 15.5 Public Score: 15.6