Closed aragakiyui611 closed 1 year ago
For the hand-only images, you should use Pose2Pose (https://github.com/mks0601/Hand4Whole_RELEASE/tree/Pose2Pose)
Yes I am using the pose2pose
mpjpe 63 is not a making sense number. it's too big. I guess there should be some bugs? How did you evaluate on ih2.6m dataset?
InterHand26M.py.txt model.py.txt I using the same code as that in the repository, my trained weights perform normally on other datasets like FreiHAND, COCO
joint_gt includes both right/left hands, while the output only includes the right hand.
Thank you! I flip back the left hands and MPJPE now is 18.21mm
Please note that for the fair comparison to previous works, you should train the network again after removing this view sampling. https://github.com/mks0601/Hand4Whole_RELEASE/blob/39fd3727ac1729c0ce59890986e41abbce0f9955/data/InterHand26M/InterHand26M.py#L56
Thank you!
Hi, I want to download the Human36M dataset you shared, but the google drive said it exceeds the download quota.
"此文件已超出下载配额,因此目前无法下载": this file have exceeded download quota, thus cannot be downloaded now.
Try this at below
Try this at below
It seems that this is the one I use, I cannot download it either
Try a trick written below
Thank you every much!
I tested the hand part of Hand4Whole and the result is
MPJPE: 63.86 mm
, is it reasonable? Did you test the model in terms of MPJPE on InterHand26M and may I know your result? Thank you!