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

Citation Author(s):: Dogancan Temel (Georgia Institute of Technology)

Jinsol Lee (Georgia Institute of Technology)

Ghassan AlRegib (Georgia Institute of Technology)
Submitted by:: Ghassan AlRegib
Last updated:: Thu, 09/30/2021 - 17:56
DOI:: 10.21227/h4fr-h268
Data Format:: *.jpg
Links:: CURE-OR GitHub

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Abstract

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-OR dataset, there are 1,000,000 images of 100 objects with varying size, color, and texture, captured with multiple devices in different setups. The majority of images in the dataset were acquired with smartphones and tested with off-the-shelf applications to benchmark the recognition performance of devices and applications that are used in our daily lives. Please refer to our GitHub page for code, papers, and more information.

Instructions:

Image name format :

"backgroundID_deviceID_objectOrientationID_objectID_challengeType_challengeLevel.jpg"

backgroundID:

1: White 2: Texture 1 - living room 3: Texture 2 - kitchen 4: 3D 1 - living room 5: 3D 2 – office

objectOrientationID:

1: Front (0 º) 2: Left side (90 º) 3: Back (180 º) 4: Right side (270 º) 5: Top

objectID:

1-100

challengeType:

No challenge 02: Resize 03: Underexposure 04: Overexposure 05: Gaussian blur 06: Contrast 07: Dirty lens 1 08: Dirty lens 2 09: Salt & pepper noise 10: Grayscale 11: Grayscale resize 12: Grayscale underexposure 13: Grayscale overexposure 14: Grayscale gaussian blur 15: Grayscale contrast 16: Grayscale dirty lens 1 17: Grayscale dirty lens 2 18: Grayscale salt & pepper noise

challengeLevel:

A number between [0, 5], where 0 indicates no challenge, 1 the least severe and 5 the most severe challenge. Challenge type 1 (no challenge) and 10 (grayscale) has a level of 0 only. Challenge types 2 (resize) and 11 (grayscale resize) has 4 levels (1 through 4). All other challenges have levels 1 to 5.