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

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

A novel curriculum model adaptation method to transfer semantic models from clear-weather condition to foggy weather condition by combining synthetic and real data. Synthetic and real fog datasets are provided.

Publications

Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding
Dengxin Dai, Christos Sakaridis, Simon Hecker and Luc Van Gool
International Journal of Computer Vision (IJCV), 2020
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