Universal Semi-Supervised Semantic Segmentation
In recent years, the need for semantic segmentation has arisen across several different applications and environments. However, the expense and redundancy of annotation often limits the quantity of labels available for training in any domain, while deployment is easier if a single model works well across domains... (read more)
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ImageNet
Cityscapes
SYNTHIA
SUN RGB-D
Taskonomy
IDD
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Methods used in the Paper
| METHOD | TYPE | |
|---|---|---|
Entropy Regularization
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Regularization |