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Found 5 papers, 2 papers with code
Calibrated Out-of-Distribution Detection with a Generic Representation
We propose a novel OOD method, called GROOD, that formulates the OOD detection as a Neyman-Pearson task with well calibrated scores and which achieves excellent performance, predicated by the use of a good generic representation.
Road Anomaly Detection by Partial Image Reconstruction With Segmentation Coupling
To that end, we propose a reconstruction module that can be used with many existing semantic segmentation networks, and that is trained to recognize and reconstruct road (drivable) surface from a small bottleneck.
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression
We obtain smaller mean distance and angular errors than state-of-the-art 6-DoF pose estimation algorithms based on direct pose regression and pose estimation from scene coordinates on all datasets.
Online Adaptive Hidden Markov Model for Multi-Tracker Fusion
We show the effectiveness of the proposed method on combination of two and three tracking algorithms.
A Novel Performance Evaluation Methodology for Single-Target Trackers
This paper addresses the problem of single-target tracker performance evaluation.
