Implement an Auto-Encoder that takes 3D Models as Input - Engineering Assignment Help

Assignment Task

Tasks
• Implement an auto-encoder that takes 3D models as input.
• Train it on ShapeNet Dataset (only cars model) and compare the results to DeepSDF.

Step 1 : Preprocessing
• Create voxel grid from deepSDF input data (better as preprocessing otherwise the training will be too slow). If more points fall on the same voxel, remember to average the SDF values.
• Be sure to verify that the voxelization is working (you can easily convert a voxel grid to a point cloud and visualise along the original input)

Step 2 : Training
• I have the code for auto decoder, so for training only “auto encoder” needs to be coded.
• Details on how to train the auto encoder can be found here and in Section 6.3 of this paper

Step 3 : Testing
• This involves reconstruction of the training dataset to see how good the training was.

Step 4 : Evaluation
• Comparison of the results with the only auto decoder model (already have the code for auto decoder)

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