BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors
Ali Harakeh,Michael Smart,Steven L. Waslander,Ali Harakeh,Michael Smart,Steven L. Waslander
When incorporating deep neural networks into robotic systems, a major challenge is the lack of uncertainty measures associated with their output predictions. Methods for uncertainty estimation in the output of deep object detectors (DNNs) have been proposed in recent works, but have had limited success due to 1) information loss at the detectors nonmaximum suppression (NMS) stage, and 2) failure t...
