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Detection and Retrieval of Out-of-Distribution Objects in Semantic
  Segmentation

Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation

14 May 2020
Philipp Oberdiek
Matthias Rottmann
G. Fink
ArXivPDFHTML

Papers citing "Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation"

8 / 8 papers shown
Title
Uncertainty and Prediction Quality Estimation for Semantic Segmentation
  via Graph Neural Networks
Uncertainty and Prediction Quality Estimation for Semantic Segmentation via Graph Neural Networks
Edgar Heinert
Stephan Tilgner
Timo Palm
Matthias Rottmann
UQCV
32
0
0
17 Sep 2024
Latency-aware Road Anomaly Segmentation in Videos: A Photorealistic
  Dataset and New Metrics
Latency-aware Road Anomaly Segmentation in Videos: A Photorealistic Dataset and New Metrics
Beiwen Tian
Huan-ang Gao
Leiyao Cui
Yupeng Zheng
Lan Luo
Baofeng Wang
Rong Zhi
Guyue Zhou
Hao Zhao
24
4
0
10 Jan 2024
Maskomaly:Zero-Shot Mask Anomaly Segmentation
Maskomaly:Zero-Shot Mask Anomaly Segmentation
J. Ackermann
Christos Sakaridis
F. I. F. Richard Yu
ISeg
16
23
0
26 May 2023
Two Video Data Sets for Tracking and Retrieval of Out of Distribution
  Objects
Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects
Kira Maag
Robin Shing Moon Chan
Svenja Uhlemeyer
K. Kowol
Hanno Gottschalk
27
19
0
05 Oct 2022
Triggering Failures: Out-Of-Distribution detection by learning from
  local adversarial attacks in Semantic Segmentation
Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation
Victor Besnier
Andrei Bursuc
David Picard
Alexandre Briot
UQCV
11
48
0
03 Aug 2021
Entropy Maximization and Meta Classification for Out-Of-Distribution
  Detection in Semantic Segmentation
Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentation
Robin Shing Moon Chan
Matthias Rottmann
Hanno Gottschalk
OODD
14
149
0
09 Dec 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,134
0
06 Jun 2015
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