Gradient-Based Quantification of Epistemic Uncertainty for Deep Object
Detectors

Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors

9 July 2021

Tobias Riedlinger

Matthias Rottmann

Marius Schubert

Hanno Gottschalk

Papers citing "Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors"

13 / 13 papers shown

Title
Revisiting Gradient-based Uncertainty for Monocular Depth Estimation Julia Hornauer Amir El-Ghoussani Vasileios Belagiannis UQCV 55 0 0 09 Feb 2025
DrIFT: Autonomous Drone Dataset with Integrated Real and Synthetic Data, Flexible Views, and Transformed Domains Fardad Dadboud Hamid Azad Varun Mehta M. Bolic Iraj Mntegh 67 0 0 06 Dec 2024
Uncertainty and Prediction Quality Estimation for Semantic Segmentation via Graph Neural Networks Edgar Heinert Stephan Tilgner Timo Palm Matthias Rottmann UQCV 36 0 0 17 Sep 2024
GIT: Detecting Uncertainty, Out-Of-Distribution and Adversarial Samples using Gradients and Invariance Transformations Julia Lust A. P. Condurache AAML UQCV 8 0 0 05 Jul 2023
LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds Tobias Riedlinger Marius Schubert Sarina Penquitt Jan-Marcel Kezmann Pascal Colling Karsten Kahl L. Roese-Koerner Michael Arnold Urs Zimmermann Matthias Rottmann 3DPC 27 1 0 13 Jun 2023
Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution Segmentation Kira Maag Tobias Riedlinger UQCV 32 7 0 13 Mar 2023
Normalizing Flow based Feature Synthesis for Outlier-Aware Object Detection Nishant Kumar Sinisa Segvic Abouzar Eslami Stefan Gumhold 41 13 0 01 Feb 2023
Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning Julian Burghoff Robin Shing Moon Chan Hanno Gottschalk Annika Muetze Tobias Riedlinger Matthias Rottmann Marius Schubert BDL 21 0 0 30 May 2022
Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data Matej Grcić Petra Bevandić Zoran Kalafatić Sinivsa vSegvić 21 10 0 23 Dec 2021
On the Importance of Gradients for Detecting Distributional Shifts in the Wild Rui Huang Andrew Geng Yixuan Li 189 328 0 01 Oct 2021
Deep Sub-Ensembles for Fast Uncertainty Estimation in Image Classification Matias Valdenegro-Toro UQCV 56 51 0 17 Oct 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015