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Found 1 papers, 1 papers with code
Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation
Training deep networks for semantic segmentation requires large amounts of labeled training data, which presents a major challenge in practice, as labeling segmentation masks is a highly labor-intensive process.
Ranked #4 on
Semi-Supervised Semantic Segmentation
on Cityscapes 100 samples labeled
(using extra training data)
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