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Efficient Multi-task Uncertainties for Joint Semantic Segmentation and
  Monocular Depth Estimation

Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation

16 February 2024
S. Landgraf
Markus Hillemann
Theodor Kapler
Markus Ulrich
    UQCV
ArXivPDFHTML

Papers citing "Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation"

6 / 6 papers shown
Title
Enhancing Monocular Depth Estimation with Multi-Source Auxiliary Tasks
Enhancing Monocular Depth Estimation with Multi-Source Auxiliary Tasks
Alessio Quercia
Erenus Yildiz
Zhuo Cao
Kai Krajsek
Abigail Morrison
Ira Assent
Hanno Scharr
51
0
0
22 Jan 2025
Optical aberrations in autonomous driving: Physics-informed parameterized temperature scaling for neural network uncertainty calibration
Optical aberrations in autonomous driving: Physics-informed parameterized temperature scaling for neural network uncertainty calibration
D. Wolf
Alexander Braun
Markus Ulrich
89
0
0
18 Dec 2024
Iterative Distillation for Better Uncertainty Estimates in Multitask
  Emotion Recognition
Iterative Distillation for Better Uncertainty Estimates in Multitask Emotion Recognition
Didan Deng
Liang Wu
Bertram E. Shi
44
32
0
21 Jul 2021
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from
  Monocular images
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images
Lei He
Jiwen Lu
Guanghui Wang
Shiyu Song
Jie Zhou
31
69
0
19 Jan 2021
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
5,652
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
9,109
0
06 Jun 2015
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