Evaluating Uncertainty Quantification for Bird’s Eye View Semantic Segmentation

Evaluating various uncertainty quantification methods for BEV semantic segmentation based on two benchmark datasets and proposing augmenting uncertainty-aware BEV semantic segmentation models with supervised camera-view semantic segmentation features suggest that exploring different types of supervision holds promise for enhancing uncertainty-aware BEV segmentation models.