The reproduced results on the Waymo dataset

[WWW2323]

Hi, dear author, there is about 0.5~1.0 gap between the results I reproduced and the results the paper reports on waymo dataset, it's variance or there is something wrong with my reproducing? Do you pre-train Voxel-MAE with 100% waymo training data? I pre-train Voxel-MAE with this config for 30 epochs and use the 30th epoch to initialize CenterPoint. After fine-tuning for 30epoch, I get the following results:

And the results reported on paper is:

[chaytonmin]

Hi, dear author, there is about 0.5~1.0 gap between the results I reproduced and the results the paper reports on waymo dataset, it's variance or there is something wrong with my reproducing? Do you pre-train Voxel-MAE with 100% waymo training data? I pre-train Voxel-MAE with this config for 30 epochs and use the 30th epoch to initialize CenterPoint. After fine-tuning for 30epoch, I get the following results: And the results reported on paper is:

We pre-train Voxel-MAE with ~20% data of training samples as OpenPCDet.

[WWW2323]

@chaytonmin Hi, dear author, thanks for your quick reply, and is my result normal? How many epochs you pre-trian Voxel-MAE? 3 or 20 or 30 epochs? The pre-train epoch in the code is 30, while the pre-train epoch mentioned in the paper is 3, is it a mistake?

[chaytonmin]

@chaytonmin Hi, dear author, thanks for your quick reply, and is my result normal? How many epochs you pre-trian Voxel-MAE? 3 or 20 or 30 epochs? The pre-train epoch in the code is 30, while the pre-train epoch mentioned in the paper is 3, is it a mistake?

The result is normal. The environmental changes can cause minor changes in results.
Voxel-MAE converges in 3 epochs on KITTI dataset. Therefore, we just pre-train for 3 epochs. With the limited time, we didn't do a lot of experiments. Maybe more epochs are more suitable.