can not reproduce same result reported in paper

[MengHao666]

Hi, I train the model following your configuration and code completely,but get much better result than in your paper

Specifically, we do experiment on Machine_annot subset, but got 10.52/15.99 for SH/IH MPJPE, which is much better than result 12.56/18.59. I am so confused about such result, as I need to compare with yours. How should I do?

[MengHao666]

Hi, when I use the 15 epoch checkpoint of Train(M) and test on Test(M), but got 10.62/16.21 for SH/IH MPJPE, which is still much better than result 12.56/18.59. I think I need to compare with the result reported in the paper , so I am now trying to find the result which checkpoint could be most close to 12.56/18.59.

Also, could you provide me with your checkpoint that could reproduce 12.56/18.59 of MPJPE. Actually, I also need to compare with the result of 2 situations (SH only or SH+IH) of train set on machine_annot subset, i.e. M not H+M, just look slike following picture. Could u provide me these checkpoints? so we could have a fair comparision.

[mks0601]

That is weird.. I haven't changed the codes and datasets after writing this paper much.
Anyway, why not just follow numbers reported in the paper? Do you need some checkpoints?

[MengHao666]

That is weird.. I haven't changed the codes and datasets after writing this paper much.
Anyway, why not just follow numbers reported in the paper? Do you need some checkpoints?

I change code of following line to trans_test = gt # gt, rootnet`, does it have some effect?

InterHand2.6M/main/config.py

Line 39 in 2b8061d

trans_test = 'rootnet' # gt, rootnet

[mks0601]

Surely it affects much. It uses GT root joint depth during inference. Please set it to rootnet.

[MengHao666]

Surely it affects much. It uses GT root joint depth during inference. Please set it to rootnet.

I am so sorry that when I set this parameter to rootnet, it get very bad result 86.15/69.97 , I think you may forget something. What should I do？ Could u give me the chekpoint to reproduce result of 12.56/18.59? I am so confused now.

[mks0601]

You'd better download the rootnet's output again. I fixed some bugs several months ago.

[MengHao666]

You'd better download the rootnet's output again. I fixed some bugs several months ago.

I will try again.

[MengHao666]

You'd better download the rootnet's output again. I fixed some bugs several months ago.

I am sorry to see that in your upatdated files,you didn't distinguish which annot_subset the rootnet's output belongs to. And all my experiment are doing on machine_annot annot_subset.

[mks0601]

Those files can be used across all subsets.