A convergent soft self-labeling framework with new Potts relaxations and a collision cross-entropy achieves state-of-the-art scribble-based semantic segmentation on standard architectures.
In 2005 IEEE computer society conference on com- puter vision and pattern recognition (CVPR’05), pages 763–
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Soft Self-labeling and Potts Relaxations for Weakly-Supervised Segmentation
A convergent soft self-labeling framework with new Potts relaxations and a collision cross-entropy achieves state-of-the-art scribble-based semantic segmentation on standard architectures.