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Thanks for sharing the code for this paper, it's a great read and really highlights some of the limitations of the state of the art.
Would it be possible to share the code example for mesh correspondence?
I see that in the paper you follow the experimental set up of Donati et. al for this task. Does this refer only to the training strategy or does it mean you also adapt their functional map correspondence architecture after acquiring features?
Thanks!
The text was updated successfully, but these errors were encountered:
We used the full functional map setup for the correspondence results in Sec 5.3. That is, we used a DiffusionNet to extract features, then those features were used as inputs to functional map correspondence, differentiating all the way back through the DiffusionNet for training.
Hi folks,
Thanks for sharing the code for this paper, it's a great read and really highlights some of the limitations of the state of the art.
Would it be possible to share the code example for mesh correspondence?
I see that in the paper you follow the experimental set up of Donati et. al for this task. Does this refer only to the training strategy or does it mean you also adapt their functional map correspondence architecture after acquiring features?
Thanks!
The text was updated successfully, but these errors were encountered: