The Cityscapes Dataset for Semantic Urban Scene Understanding
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Cites background or methods from "The Cityscapes Dataset for Semantic..."
...Cityscapes [6] is a recently released dataset for semantic urban scene understanding....
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...We evaluate it in this section on three different datasets, including ImageNet scene parsing challenge 2016 [43], PASCAL VOC 2012 semantic segmentation [8] and urban scene understanding dataset Cityscapes [6]....
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...It is the champion of ImageNet scene parsing challenge 2016 [43], and arrived the 1st place on PASCAL VOC 2012 semantic segmentation benchmark [8], and the 1st place on urban scene Cityscapes data [6]....
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...The performance can be improved by increasing the iteration number, which is set to 150K for ImageNet experiment, 30K for PASCAL VOC and 90K for Cityscapes....
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Cites background from "The Cityscapes Dataset for Semantic..."
...Models based on Fully Convolutional Networks (FCNs) [64, 49] have demonstrated significant improvement on several segmentation benchmarks [17, 52, 13, 83, 5]....
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...Semantic segmentation with the goal to assign semantic labels to every pixel in an image [17, 52, 13, 83, 5] is one of the fundamental topics in computer vision....
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References
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"The Cityscapes Dataset for Semantic..." refers methods in this paper
...We adopted VGG16 [68] and utilize the PASCAL-context setup [41] with a modified learning rate to match our image resolution under an unnormalized loss....
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