CURE-OR: Challenging Unreal and Real Environment for Object Recognition

As one of the research directions at OLIVES Lab @ Georgia Tech, we focus on the robustness of data-driven algorithms under diverse challenging conditions where trained models can possibly be depolyed. To achieve this goal, we introduced a large-sacle (1.M images) object recognition dataset (CURE-OR) which is among the most comprehensive datasets with controlled synthetic challenging conditions. In CURE

DOI Link:

10.21227/h4fr-h268

Links:

CURE-OR GitHub

Cite

Color images - Challenge-free
Color images - Challenge: resizing
Color images - Challenge: underexposure
Color images - Challenge: overexposure
Color images - Challenge: blur
Color images - Challenge: contrast
Color images - Challenge: dirty lens1
Color images - Challenge: dirty lens2
Color images - Challenge: salt&pepper
Grayscale images - Challenge-free
Grayscale images - Challenge: resizing
Grayscale images - Challenge: underexposure
Grayscale images - Challenge: overexposure
Grayscale images - Challenge: blur
Grayscale images - Challenge: contrast
Grayscale images - Challenge: dirty lens1
Grayscale images - Challenge: dirty lens2
Grayscale images - Challenge: salt&pepper

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Documentation:

CURE-OR ReadMe.pdf

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[1] Dogancan Temel, Jinsol Lee, Ghassan AlRegib, "CURE-OR: Challenging Unreal and Real Environment for Object Recognition", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/h4fr-h268. Accessed: Feb. 10, 2025.

@data{h4fr-h268-19,
doi = {10.21227/h4fr-h268},
url = {http://dx.doi.org/10.21227/h4fr-h268},
author = {Dogancan Temel; Jinsol Lee; Ghassan AlRegib },
publisher = {IEEE Dataport},
title = {CURE-OR: Challenging Unreal and Real Environment for Object Recognition},
year = {2019} }

TY - DATA
T1 - CURE-OR: Challenging Unreal and Real Environment for Object Recognition
AU - Dogancan Temel; Jinsol Lee; Ghassan AlRegib
PY - 2019
PB - IEEE Dataport
UR - 10.21227/h4fr-h268
ER -

Dogancan Temel, Jinsol Lee, Ghassan AlRegib. (2019). CURE-OR: Challenging Unreal and Real Environment for Object Recognition. IEEE Dataport. http://dx.doi.org/10.21227/h4fr-h268

Dogancan Temel, Jinsol Lee, Ghassan AlRegib, 2019. CURE-OR: Challenging Unreal and Real Environment for Object Recognition. Available at: http://dx.doi.org/10.21227/h4fr-h268.

Dogancan Temel, Jinsol Lee, Ghassan AlRegib. (2019). "CURE-OR: Challenging Unreal and Real Environment for Object Recognition." Web.

1. Dogancan Temel, Jinsol Lee, Ghassan AlRegib. CURE-OR: Challenging Unreal and Real Environment for Object Recognition [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/h4fr-h268

Dogancan Temel, Jinsol Lee, Ghassan AlRegib. "CURE-OR: Challenging Unreal and Real Environment for Object Recognition." doi: 10.21227/h4fr-h268

Dataset Files