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MODEL ZOO

Common settings and notes

  • The experiments are run with PyTorch 1.7.0, CUDA 10.1 and CUDNN 7.6
  • The training is conducted on 8 Telsa V100 GPUs

Waymo 3D Detection

We try a few training schedules for TransFusion-L and list the performance below. The fusion-based models are further trained for 6 epochs from the pretrained LiDAR backbone. We freeze the weight of LiDAR backbone to save GPU memory.

Model Backbone epoch Veh_L2 Ped_L2 Cyc_L2 MAPH
TransFusion-L VoxelNet 12 63.86 62.84 67.17 64.63
TransFusion-L VoxelNet 24 64.54 63.39 66.43 64.78
TransFusion-L VoxelNet 36 65.07 63.70 65.97 64.91
TransFusion VoxelNet 36 + 6 65.11 64.02 67.40 65.51