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Abstract
In this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images from thermal cameras has significantly improved. As a side effect, we noticed that Style Transfer can be also used to improve detection accuracy from standard RGB camera, which has potential for various applications.
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language:
- English
- Publication year:
- 2019
- Bibliographic description:
- Cygert S., Czyżewski A.: Style Transfer for Detecting Vehicles with Thermal Camera// / : , 2019,
- Sources of funding:
- Verified by:
- Gdańsk University of Technology
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