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Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context
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Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context

Shashank Agnihotri
Julia Grabinski
Margret Keuper
ArXiv (abs)PDFHTML

Papers citing "Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context"

2 / 2 papers shown
Title
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training
Tejaswini Medi
Steffen Jung
Margret Keuper
AAML
94
3
0
30 Oct 2024
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCLSSL
342
4,109
0
17 Jun 2020