RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers
The 3D deep learning community has seen significant strides in pointcloud processing over the last few years. However, the datasets on which deep models have been trained have largely remained the same...
Most datasets comprise clean, clutter-free pointclouds canonicalized for pose. Models trained on these datasets fail in uninterpretible and unintuitive ways when presented with data that contains transformations “unseen” at train time. While data augmentation enables models to be robust to “previously seen” input transformations, 1) we show that this does not work for unseen transformations during inference, and 2) data augmentation makes it difficult