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Time for a Background Check! Uncovering the impact of Background
  Features on Deep Neural Networks

Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks

24 June 2020
Vikash Sehwag
Rajvardhan Oak
M. Chiang
Prateek Mittal
    FAtt
ArXivPDFHTML

Papers citing "Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks"

2 / 2 papers shown
Title
Generating High Fidelity Data from Low-density Regions using Diffusion
  Models
Generating High Fidelity Data from Low-density Regions using Diffusion Models
Vikash Sehwag
C. Hazirbas
Albert Gordo
Firat Ozgenel
Cristian Canton Ferrer
DiffM
33
66
0
31 Mar 2022
Characterizing and Improving the Robustness of Self-Supervised Learning
  through Background Augmentations
Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations
Chaitanya K. Ryali
D. Schwab
Ari S. Morcos
SSL
29
9
0
23 Mar 2021
1