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Hello! Thank you for sharing your method, and I have some questions about SHREC 2017 track 1.
In the track report of track1, you mentioned that RotationNet uses 3308 CAD models in ShapeNetSem for training. Then you fine-tune the model using 830 objects in SceneNN.
I wander to know how to render objects in SNN(RGB-D objects in *.ply format) into 20 views.
And would you mind teling me your network parameters setting in track1, like batchsize, learning rate..?
Looking forward to your reply!
The text was updated successfully, but these errors were encountered:
Hello! Thank you for sharing your method, and I have some questions about SHREC 2017 track 1.
In the track report of track1, you mentioned that RotationNet uses 3308 CAD models in ShapeNetSem for training. Then you fine-tune the model using 830 objects in SceneNN.
I wander to know how to render objects in SNN(RGB-D objects in *.ply format) into 20 views.
And would you mind teling me your network parameters setting in track1, like batchsize, learning rate..?
Looking forward to your reply!
The text was updated successfully, but these errors were encountered: