Deep Evidential Uncertainty Estimation for Semantic Segmentation under Out-Of-Distribution Obstacles
Abstract: In order to navigate safely and reliably in novel environments, robots must estimate perceptual uncertainty when confronted with out-of-distribution (OOD) obstacles not seen in training data ...
Abstract: Semi-supervised object detection (SSOD) aims to solve the data annotation challenge in object detection and can achieve remarkable progress in natural scenes; however, it remains unexplored ...
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