yinjunbo / ssda3d Goto Github PK

I didn't find your trained model, could you share them?

Hi, thanks for sharing the code for your project!

In the paper there are comparisons with ST3D in both UDA and SSDA settings. I have a few questions about these experiments.

• Since this repository does not seem to contain code related to ST3D, did you modify the official ST3D release to use CenterPoint?
• For waymo->nuscenes experiments, the ST3D configuration has pseudo-label updates disabled (UPDATE_PSEUDO_LABEL_INTERVAL=1000), were you using the same settings as them?

Hello, thanks for your great work.
I found some differences between the code and paper. According to the paper, "before merging the 3D boxes, collision detection will be performed". But in the intra_domain_point_mixup function, the "gt_boxes" were merged directly. This may cause some problems.

Hi, authors. Thanks for your great work.

Do you have exact date for releasing the code?

Hi, are the map/nds results you reported for nusc a direct multiplication by 10 on top of the original metric?

Also it seems that there is no comparison with the results of source only + labeled target data （finetune）?

Thanks for sharing this excellent work! Could you please share the details about how the 2nd stage works under 100% labeled target setting? In this case, there will be no TU data, will the student-teacher learning still be conducted? Thanks in advance!

How did you generate the partial_info_data (1%, 5%, 10%, 20%)? For example, for the 1% data, did you take the first 1% of the info from the complete info.pkl file and split it into the top 1% and the last 99% of the pkl file? Or did you randomly sample 1% of the total amount of samples?

I have seen that the nds score reported is for all the categories, not for the car only.