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. Fig, Semantic segmentation produced by the different models The first 2 columns correspond to test images from Virtual KITTI, while and the last 2 columns correspond to images from our KITTI test. The first row shows the input RGB image, followed by depth, groundtruth labels. Rows 4 th to 7 th show the segmentation produced by SegNet2 (RGB-D) and SegNet (RGB) respectively. The 8 th row shows the border regions from the ground truth, which are used to evaluate border recall and our metric in eq, CEDCNN (RGB) The 9 th row shows the border precision of CEDCNN2 (RGB-D), p.2

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