Jeonghwan Kim

I used the metric in Python

Thank you for your answer I saved the mesh as obj and check between the data what you provided. but, I got the exactly opposite results as the image shown....

``` smplr = SMPLR() params_dir = "../dataset/THuman/THuman2.0_smplx/0525/smplx_param.pkl" db = np.load(params_dir, allow_pickle=True) dict_ = {} for key in db: dict_[key] = torch.tensor(db[key]) global_ori = torch.from_numpy(dict_["global_orient"])[0] pose = torch.cat([global_ori, torch.from_numpy(dict_["body_pose"][0])],0) verts =...

I think the SMPL regressor is based on vibe form. That's why the verts show the opposite. Thank you

Thank you, And I have another question If I follow the config v1.yml and config v1_hrnet_3dpw_ft.yml, then can I reproduce the model as protocol 3*??

Thank you, Is it protocol 3 or protocol 3*?? And, Are these two different in pretraining processes??

OK, I'll try it I'm really thank you for your help.

Thank you. I'll tell you when I find out why.

I found it!! its because of the 'match_preds_to_gts_for_supervision' argument. In evaluation config the 'match_preds_to_gts_for_supervision' was set to false Thank u.