3260 papers • 126 benchmarks • 313 datasets
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These leaderboards are used to track progress in aerial-video-semantic-segmentation-9
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Use these libraries to find aerial-video-semantic-segmentation-9 models and implementations
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The proposed research work modifies the CNN architecture by incorporating temporal information to improve the efficiency of video semantic segmentation and produced promising results even for the pretrained model of UVid-Net on urban street scene by fine tuning the final layer on UAV aerial videos.
Adding a benchmark result helps the community track progress.