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FSNet: A Failure Detection Framework for Semantic Segmentation

FSNet: A Failure Detection Framework for Semantic Segmentation

19 August 2021
Q. Rahman
Niko Sünderhauf
Peter Corke
Feras Dayoub
    UQCV
    SSeg
ArXivPDFHTML

Papers citing "FSNet: A Failure Detection Framework for Semantic Segmentation"

10 / 10 papers shown
Title
System-Level Safety Monitoring and Recovery for Perception Failures in
  Autonomous Vehicles
System-Level Safety Monitoring and Recovery for Perception Failures in Autonomous Vehicles
Kaustav Chakraborty
Zeyuan Feng
Sushant Veer
Apoorva Sharma
B. Ivanovic
Marco Pavone
Somil Bansal
29
1
0
26 Sep 2024
Towards Ground-truth-free Evaluation of Any Segmentation in Medical
  Images
Towards Ground-truth-free Evaluation of Any Segmentation in Medical Images
Ahjol Senbi
Tianyu Huang
Fei Lyu
Qing Li
Yuhui Tao
...
Qiang Chen
Chengyan Wang
Shuo Wang
Tao Zhou
Yizhe Zhang
MedIm
26
1
0
23 Sep 2024
SQA-SAM: Segmentation Quality Assessment for Medical Images Utilizing
  the Segment Anything Model
SQA-SAM: Segmentation Quality Assessment for Medical Images Utilizing the Segment Anything Model
Yizhe Zhang
Shuo Wang
Tao Zhou
Qingquan Dou
D. Z. Chen
27
1
0
15 Dec 2023
Task-Aware Risk Estimation of Perception Failures for Autonomous
  Vehicles
Task-Aware Risk Estimation of Perception Failures for Autonomous Vehicles
Pasquale Antonante
Sushant Veer
Zheng Li
Xinshuo Weng
Luca Carlone
Marco Pavone
49
9
0
03 May 2023
Failure Detection for Motion Prediction of Autonomous Driving: An
  Uncertainty Perspective
Failure Detection for Motion Prediction of Autonomous Driving: An Uncertainty Perspective
Wenbo Shao
Yan Xu
Liang Peng
Jun Li
Hong Wang
24
15
0
11 Jan 2023
CNN based Intelligent Streetlight Management Using Smart CCTV Camera and
  Semantic Segmentation
CNN based Intelligent Streetlight Management Using Smart CCTV Camera and Semantic Segmentation
Md Sakib Ullah Sourav
Huidong Wang
Mohammad Raziuddin Chowdhury
R. Sulaiman
16
0
0
18 Sep 2022
Monitoring of Perception Systems: Deterministic, Probabilistic, and
  Learning-based Fault Detection and Identification
Monitoring of Perception Systems: Deterministic, Probabilistic, and Learning-based Fault Detection and Identification
Pasquale Antonante
Heath Nilsen
Luca Carlone
37
24
0
22 May 2022
See Yourself in Others: Attending Multiple Tasks for Own Failure
  Detection
See Yourself in Others: Attending Multiple Tasks for Own Failure Detection
Bo Sun
Jiaxu Xing
Hermann Blum
Roland Siegwart
César Cadena
34
12
0
06 Oct 2021
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey
  of Emerging Trends
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends
Q. Rahman
Peter Corke
Feras Dayoub
OOD
27
51
0
05 Jan 2021
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
279
9,136
0
06 Jun 2015
1