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Identifying Label Errors in Object Detection Datasets by Loss Inspection

Identifying Label Errors in Object Detection Datasets by Loss Inspection

13 March 2023
Marius Schubert
Tobias Riedlinger
Karsten Kahl
Daniel Kröll
S. Schoenen
Sinisa Segvic
Matthias Rottmann
    NoLa
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Papers citing "Identifying Label Errors in Object Detection Datasets by Loss Inspection"

4 / 4 papers shown
Title
RePOPE: Impact of Annotation Errors on the POPE Benchmark
RePOPE: Impact of Annotation Errors on the POPE Benchmark
Yannic Neuhaus
Matthias Hein
27
0
0
22 Apr 2025
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
C. Kim
Sangwoo Moon
Jihwan Moon
Dongyeon Woo
Gunhee Kim
NoLa
57
0
0
25 Feb 2025
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations
David Tschirschwitz
Volker Rodehorst
26
1
0
14 Sep 2024
Deep Active Learning with Noisy Oracle in Object Detection
Deep Active Learning with Noisy Oracle in Object Detection
Marius Schubert
Tobias Riedlinger
Karsten Kahl
Matthias Rottmann
ObjD
20
1
0
30 Sep 2023
1