PointMask: Towards Interpretable and Bias-Resilient Point Cloud Processing

1 code implementation • 9 Jul 2020 • Saeid Asgari Taghanaki, Kaveh Hassani, Pradeep Kumar Jayaraman, Amir Hosein Khasahmadi, Tonya Custis

We show that coupling a PointMask layer with an arbitrary model can discern the points in the input space which contribute the most to the prediction score, thereby leading to interpretability.

3D Point Cloud Classification Robust classification

Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders

no code implementations • 12 May 2020 • Saeid Asgari Taghanaki, Mohammad Havaei, Alex Lamb, Aditya Sanghi, Ara Danielyan, Tonya Custis

The latent variables learned by VAEs have seen considerable interest as an unsupervised way of extracting features, which can then be used for downstream tasks.