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

Semantic segmentation has been widely investigated in the community, in which the state of the art techniques are based on supervised models. Those models have reported unprecedented performance at the cost of requiring a large set of high quality segmentation masks. To obtain such annotations is hi...

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Veröffentlicht in:	arXiv.org 2022-01
Hauptverfasser:	Rihuan Ke, Aviles-Rivero, Angelica, Pandey, Saurabh, Reddy, Saikumar, Schönlieb, Carola-Bibiane
Format:	Artikel
Sprache:	eng
Schlagworte:	Consistency Image annotation Masks Semantic segmentation Semantics Statistical analysis Training Uncertainty
Online-Zugang:	Volltext
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