Fast and Simple Explainability for Point Cloud Networks

arXiv:2403.07706v1 Announce Type: cross
Abstract: We propose a fast and simple explainable AI (XAI) method for point cloud data. It computes pointwise importance with respect to a trained network downstream task. This allows better understanding of the network properties, which is imperative for safety-critical applications. In addition to debugging and visualization, our low computational complexity facilitates online feedback to the network at inference. This can be used to reduce uncertainty and to increase robustness. In this work, we introduce \emph{Feature …

abstract applications arxiv cloud cloud data cs.cv cs.lg data debugging explainability explainable ai importance network networks safety safety-critical simple type understanding visualization xai