Comments (2)
As described in http://shapenet.cs.stanford.edu/shrec16/, We use the ShapeNetCore subset of ShapeNet which contains about 51,300 3D models over 55 common categories, each subdivided into several subcategories. We created a 70%/10%/20% training/validation/test split from this dataset.
Therefore, it should be 35,708 (70%) for training, 5,158 (10%) shapes for validation and 10,261 (20%) shapes for testing. (This is suggested by PointCloudDatasets, they claimed that in official document there should be 51,190 shapes in total, but 63 shapes are missing in original downloaded ShapeNetCore.v2 dataset)
I was wondering how to fair compare with your's result by using PointCloudDatasets, should I use the training set (35,708) for training and the validation set(5158) for testing? Or use the testing set(10261) for testing?
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FYI, SHREC16 is from http://shapenet.cs.stanford.edu/shrec16/
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Related Issues (20)
- The code for shape retrieval HOT 1
- Where is the code to reduce model oscillation ? HOT 1
- Question about the SR16 dataset. HOT 1
- ValueError: need at least one array to concatenate HOT 3
- A RuntimeError HOT 4
- Question about the normal feature
- How do you achieve end-to-end? HOT 1
- Could you please share the code for shape retrieval? I will cite your work and compare with your results. Thank you!
- NameError: name 'cls_pc_raw' is not defined HOT 2
- How to augment custom data? HOT 1
- Generated samples
- Runtime Error
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