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Narrowing the Gap: Improved Detector Training with Noisy Location
  Annotations

Narrowing the Gap: Improved Detector Training with Noisy Location Annotations

12 June 2022
Shaoru Wang
Jin Gao
Bing Li
Weiming Hu
    ObjD
    NoLa
ArXivPDFHTML

Papers citing "Narrowing the Gap: Improved Detector Training with Noisy Location Annotations"

4 / 4 papers shown
Title
In Defense and Revival of Bayesian Filtering for Thermal Infrared Object
  Tracking
In Defense and Revival of Bayesian Filtering for Thermal Infrared Object Tracking
Peng Gao
Shi-Min Li
Feng Gao
Fei Wang
Ruyue Yuan
Hamido Fujita
42
8
0
27 Feb 2024
Towards Building Self-Aware Object Detectors via Reliable Uncertainty
  Quantification and Calibration
Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration
Kemal Oksuz
Thomas Joy
P. Dokania
UQCV
23
16
0
03 Jul 2023
Combating noisy labels in object detection datasets
Combating noisy labels in object detection datasets
K. Chachula
Jakub Lyskawa
Bartlomiej Olber
Piotr Fratczak
A. Popowicz
Krystian Radlak
NoLa
31
4
0
25 Nov 2022
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
368
5,811
0
29 Apr 2021
1