MFNet
Introduced by Ha et al. in MFNet: Towards real-time semantic segmentation for autonomous vehicles with multi-spectral scenes
The first RGB-Thermal urban scene image dataset with pixel-level annotation. We published this new RGB-Thermal semantic segmentation dataset in support of further development of autonomous vehicles in the future. This dataset contains 1569 images (820 taken at daytime and 749 taken at nighttime). Eight classes of obstacles commonly encountered during driving (car, person, bike, curve, car stop, guardrail, color cone, and bump) are labeled in this dataset.
Benchmarks
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MFN Dataset
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HAPNet
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Papers
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