Self-supervised training bugs

[JXZxiao5]

Thanks for the great project. When I reproduced the self-supervised experiment, there was a gap between our results and those published in the paper. There may be bugs in the code regarding self-supervised training. Can you provide logs or models on self-supervised training?

[gxd1994]

Thank you for your attention to our work.
You can train with 8 GPUs. Better results can be obtained. It may have a randomness, you can run it again.

[gxd1994]

If you want to get higher performance in the setting of 40000 points, you can choose to retrain, or only perform finetune in the second stage using 40000 points.

[JXZxiao5]

If you want to get higher performance in the setting of 40000 points, you can choose to retrain, or only perform finetune in the second stage using 40000 points.

Yes, I do that, but it cannot work due to the heavy cost of memory on 40K points. I levarage the supervised pre-trained model relaeased to conduct the experiments in the setting of 10K, 20K, 25K, 40K points, and find that EPE3D metrics are also increasing as the number of points increases. I don't know if there is something wrong with my experiments and how I can explain it.