Datasets
Open Access
CURE-OR: Challenging Unreal and Real Environment for Object Recognition
- Citation Author(s):
- Submitted by:
- Ghassan AlRegib
- Last updated:
- Thu, 09/30/2021 - 13:56
- DOI:
- 10.21227/h4fr-h268
- Data Format:
- Links:
- License:
1763 Views- Categories:
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.
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.
Dataset Files
Color images - Challenge-free 01_no_challenge.tar.gz (1.56 GB)- Color images - Challenge: resizing 02_resize.tar.gz (3.30 GB)
- Color images - Challenge: underexposure 03_underexposure.tar.gz (3.65 GB)
- Color images - Challenge: overexposure 04_overexposure.tar.gz (5.51 GB)
- Color images - Challenge: blur 05_blur.tar.gz (2.46 GB)
- Color images - Challenge: contrast 06_contrast.tar.gz (8.06 GB)
- Color images - Challenge: dirty lens1 07_dirtylens1.tar.gz (16.04 GB)
- Color images - Challenge: dirty lens2 08_dirtylens2.tar.gz (15.64 GB)
- Color images - Challenge: salt&pepper 09_saltpepper.tar.gz (44.22 GB)
- Grayscale images - Challenge-free 10_grayscale_no_challenge.tar.gz (1.38 GB)
- Grayscale images - Challenge: resizing 11_grayscale_resize.tar.gz (2.90 GB)
- Grayscale images - Challenge: underexposure 12_grayscale_underexposure.tar.gz (3.18 GB)
- Grayscale images - Challenge: overexposure 13_grayscale_overexposure.tar.gz (4.21 GB)
- Grayscale images - Challenge: blur 14_grayscale_blur.tar.gz (1.86 GB)
- Grayscale images - Challenge: contrast 15_grayscale_contrast.tar.gz (6.30 GB)
- Grayscale images - Challenge: dirty lens1 16_grayscale_dirtylens1.tar.gz (15.27 GB)
- Grayscale images - Challenge: dirty lens2 17_grayscale_dirtylens2.tar.gz (14.56 GB)
- Grayscale images - Challenge: salt&pepper 18_grayscale_saltpepper.tar.gz (37.86 GB)
Open Access dataset files are accessible to all logged in users. Don't have a login? Create a free IEEE account. IEEE Membership is not required.
Documentation
| Attachment | Size |
|---|---|
 CURE-OR ReadMe.pdf | 5.59 MB |
