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CURE-TSD

Challenging Unreal and Real Environments for Traffic Sign Detection

CURE-TSD

The video sequences in the CURE-TSD dataset are grouped into two classes: real data and unreal data. Real data correspond to processed versions of sequences acquired from real world. Unreal data corresponds to synthesized sequences generated in a virtual environment. There are 49 real sequences and 49 unreal sequences that do not include any specific challenge. We separated the sequences into 70% and %30 splits. Therefore, we have 34 training videos and 15 test videos in both real and unreal sequences that are challenge-free. There are 300 frames in each video sequence. There are 49 challenge-free real video sequences processed with 12 different types of effects and 5 different challenge levels, which result in 2,989 (49125+49) video sequences. Moreover, there are 49 synthesized video sequences processed with 11 different types of effects and 5 different challenge levels, which leads to 2,744 (49115+49) video sequences. In total, there are 5,733 video sequences, which include around 1.72 million frames.

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OLIVES Lab, Georgia Institute of Technology
https://www.gatech.edu
Task
Object Detection
Annotation Types
Bounding Boxes
2989
Items
2
Classes
2989
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
Research Only
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