A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation

1 code implementation • 1 Dec 2020 • Rihuan Ke, Angelica Aviles-Rivero, Saurabh Pandey, Saikumar Reddy, Carola-Bibiane Schönlieb

The key idea of our technique is the extraction of the pseudo-masks statistical information to decrease uncertainty in the predicted probability whilst enforcing segmentation consistency in a multi-task fashion.

Segmentation Semi-Supervised Semantic Segmentation