Can not reproduce the result of ICP(97%)
CodeLHY opened this issue · 5 comments
@ethnhe This is really a nice work, however, when I tried to reproduce the result of FFB6D+ICP using the ICP code from PVN3D I can not reproduce the result, can you give me a hand?
https://github.com/ethnhe/PVN3D/blob/9a5481a82af4eb89fa8e0ab10ba22b9077b4652e/pvn3d/eval_icp.py#L124
It seems that you are using the ground truth mask for ICP refinement.
No, as illustrated in A.3. Implementation: PVN3D+ICP in our paper, we use the post-processed predicted mask for the whole images, using the fill label function. https://github.com/ethnhe/PVN3D/blob/9a5481a82af4eb89fa8e0ab10ba22b9077b4652e/pvn3d/eval_icp.py#L429
This procedure is slow so we pre-process and store it in a data structure. We use CPU clusters to speed up.
No, as illustrated in A.3. Implementation: PVN3D+ICP in our paper, we use the post-processed predicted mask for the whole images, using the fill label function. https://github.com/ethnhe/PVN3D/blob/9a5481a82af4eb89fa8e0ab10ba22b9077b4652e/pvn3d/eval_icp.py#L429 This procedure is slow so we pre-process and store it in a data structure. We use CPU clusters to speed up.
Thank you for your quick reply, and I really appreciate PVN3D and FFB6D, both of them are excellent and solid. Good night.
Hi @ethnhe , I followed your instruction but still get a lower result, so I reopened this issue.
Average of all object:
***************add: 87.39481105187926
***************adds: 95.32809689468347
***************add(-s): 91.22332797027117
All object (following PoseCNN):
***************add: 87.82876641272729
***************adds: 95.32953369790825
***************add(-s): 90.4528140615951
could you please provide the files needed for eval_icp.py?