Neighborhood Spatial Aggregation MC Dropout for Efficient Uncertainty-aware Semantic Segmentation in Point Clouds. (arXiv:2201.07676v1 [cs.CV])

Uncertainty-aware semantic segmentation of the point clouds includes the
predictive uncertainty estimation and the uncertainty-guided model
optimization. One key challenge in the task is the efficiency of point-wise
predictive distribution establishment. The widely-used MC dropout establishes
the distribution by computing the standard deviation of samples using multiple
stochastic forward propagations, which is time-consuming for tasks based on
point clouds containing massive points. Hence, a framework embedded with NSA-MC
dropout, a variant of MC dropout, is proposed to establish distributions in …

arxiv cv segmentation semantic uncertainty