Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding

Dengxin Dai; Christos Sakaridis; Simon Hecker; Luc Van Gool

doi:10.1007/s11263-019-01182-4

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JOURNAL ARTICLE

Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding

Dengxin Dai Christos Sakaridis Simon Hecker Luc Van Gool

Year: 2019 Journal: International Journal of Computer Vision Vol: 128 (5)Pages: 1182-1204 Publisher: Springer Science+Business Media

DOI: 10.1007/s11263-019-01182-4

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Keywords:

Computer science Adverse weather Segmentation Synthetic data Artificial intelligence Adaptation (eye) Pixel Computer vision Pattern recognition (psychology) Meteorology

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129

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7.91

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0.98

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Is in top 10%

Citation History

Topics

Image Enhancement Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding

Metrics

Citation History

Topics

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