Open Xxxkkkkx opened 2 months ago
I did not encounter such a problem. After some research on this issues, I have two things to confirm: 1) are you using sparse tensor? 2) can you try making all tensor continuous (.continuous() in PyTorch) before sending to the chamfer function.
PyTorch3D also provides an implementation of Chamfer distance, which might be more robust than the one that I used. You could try this version. https://pytorch3d.readthedocs.io/en/latest/modules/loss.html
Please let me know if the above solutions are not able to resolve this issues
During the training process, I keep encountering the following error. I have checked the format of xyz1 and xyz2 inputs to ChamferFunction, which are (32, 640, 3) and (32, 1280, 3) respectively, and they seem to be correct. I would like to consult on possible solutions. Looking forward to your response.