ICCVW-2023-Papers Application Uncertainty Estimation for Computer Vision Title Repo Paper Video A Simple and Explainable Method for Uncertainty Estimation using Attribute Prototype Networks ➖ ➖ A Unified Approach to Learning with Label Noise and Unsupervised Confidence Approximation ➖ ➖ Adversarial Attacks Against Uncertainty Quantification ➖ ➖ Biased Class Disagreement: Detection of Out of Distribution Instances by using Differently Biased Semantic Segmentation Models ➖ ➖ Calibrated Out-of-Distribution Detection with a Generic Representation ➖ DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport ➖ ➖ Distance Matters for Improving Performance Estimation Under Covariate Shift ➖ Dual-Level Interaction for Domain Adaptive Semantic Segmentation ➖ Exploring Inlier and Outlier Specification for Improved Medical OOD Detection ➖ Far Away in the Deep Space: Dense Nearest-Neighbor-based Out-of-Distribution Detection ➖ Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers ➖ Identifying Out-of-Domain Objects with Dirichlet Deep Neural Networks ➖ ➖ Probabilistic MIMO U-Net: Efficient and Accurate Uncertainty Estimation for Pixel-Wise Regression ➖ Uncle-SLAM: Uncertainty Learning for Dense Neural SLAM ➖