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Autoencoder for Point Clouds

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I was wondering, if fine-tuning the encoder part on ModelNet40 would help increase the performance over the top of PointNet?

I run the program on the dataset given, but the result seems that validation error is less than training error. This is quite strange since there is no dropout in...

the input data and the output data is same,how to deal with the data to the unregular point cloud.

i want to ask one thing is this method could be used for scene segmentation?

- do code cleaning, trim trailing space etc. - update code to support python3 - do some binary file cleaning - add clean script `clean.sh` - update `tf_ops` building script