Closed zhixuanli closed 7 months ago
You are right! The commands in stage 2 should be 'trainmesh*.sh'. Thank you for pointing out this and I have corrected it. We used 'MPII3D' as the short name of 'MPI-INF-3DHP' and you can find the codes here.
Thanks for your fast reply. Now I know how to train the second stage. Thanks!
For the second question, I believe this API code in your link is very helpful. But the ".yml" files for this MPII3D dataset are missing, which makes me not know how to set the hyper-parameters or something else. Could you please add them when you have time?
Have a good night!
Thanks for your fast reply. Now I know how to train the second stage. Thanks!
For the second question, I believe this API code in your link is very helpful. But the ".yml" files for this MPII3D dataset are missing, which makes me not know how to set the hyper-parameters or something else. Could you please add them when you have time?
Have a good night!
The training datasets for mpii3d are mixed datasets, the same as 3dpw. It can directly use the checkpoints of 3dpw to test ('bash test_mesh_mpii3d.sh'), thus there is no training script for mpii3d.
Thank you for solving all my questions. Hopes everything is fine! :)
Thanks for your awesome codes!
I find that the training commands for the first and second stages are the same, leaving the
train_mesh_h36m.sh
andtrain_mesh_3dpw.sh
not used. Is this correct?Here's the current version of the README commands:
Stage 1 (optional): Train the 3D pose estimation stream or you can directly use our pre-traind pose model
./experiment/pretrained/pose_*.pth.tar
for Stage 2.Stage 2: To train the all network for final mesh. Configs of the experiments can be found and edited in
./config
folder. Changeposenet_path
in./config/train_mesh_*.yml
to the path of the pre-trained pose model.(Second question)
BTW, since there are three datasets used in the paper, could you please release the codes for the "MPI-INF-3DHP" dataset? Thanks for your brilliant work! And looking forward for your replying.