DUS
Daimler Urban Segmentation
ImagesVideos
The Daimler Urban Segmentation Dataset is a dataset for semantic segmentation. It consists of video sequences recorded in urban traffic. The dataset consists of 5000 rectified stereo image pairs with a resolution of 1024x440. 500 frames (every 10th frame of the sequence) come with pixel-level semantic class annotations into 5 classes: ground, building, vehicle, pedestrian, sky. Dense disparity maps are provided as a reference, however these are not manually annotated but computed using semi-global matching (sgm).
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Dusha Crowd/Emotion Recognition/Macro F1Dusha Crowd/Emotion Recognition/UADusha Crowd/Emotion Recognition/WADusha Crowd/Speech Emotion Recognition/Macro F1Dusha Crowd/Speech Emotion Recognition/UADusha Crowd/Speech Emotion Recognition/WADusha Podcast/Emotion Recognition/Macro F1Dusha Podcast/Emotion Recognition/UADusha Podcast/Emotion Recognition/WADusha Podcast/Speech Emotion Recognition/Macro F1Dusha Podcast/Speech Emotion Recognition/UADusha Podcast/Speech Emotion Recognition/WA