Combining adversarial feature matching, discriminator-based self-training, and a Mean Teacher multi-label classifier improves semi-supervised semantic segmentation, reaching new state-of-the-art results on three benchmarks.
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Semi-Supervised Semantic Segmentation with High- and Low-level Consistency
Combining adversarial feature matching, discriminator-based self-training, and a Mean Teacher multi-label classifier improves semi-supervised semantic segmentation, reaching new state-of-the-art results on three benchmarks.