Apply semi-supervised learning for semantic segmentation

Generalization

Augmentation examples
  • AutoAugment is a method which uses reinforcement learning style policy search to find the optimal set of augmentations.
  • RandAugment does not apply a searching method, but instead applies augmentations randomly for each batch. This methods seems to have the similar performance but with less computational overhead.

Semi-supervised learning

UDA model

Applying it for semantic segmentation

Input image — predicted image — ground truth

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Deep Learning and AI solutions from Budapest University of Technology and Economics. http://smartlab.tmit.bme.hu/

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Deep Learning and AI solutions from Budapest University of Technology and Economics. http://smartlab.tmit.bme.hu/

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