Jun 2, 2021 · In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra unlabeled data.
In this paper, we study the semi-supervised semantic seg- mentation problem via exploring both labeled data and ex- tra unlabeled data.
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision by Xiaokang Chen 1 , Yuhui Yuan 2 , Gang Zeng 1 , Jingdong Wang 2.
In this paper, we study the semi-supervised semantic seg- mentation problem via exploring both labeled data and ex- tra unlabeled data.
In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra unlabeled data.
This paper proposes a novel consistency regularization approach, called cross pseudo supervision (CPS), which imposes the consistency on two segmentation ...
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View recent discussion. Abstract: In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra ...
Jun 2, 2021 · In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra unlabeled data.
A new semi-supervised algorithm is proposed to leverage both labeled and unlabeled data through a cross-teacher-pseudo-supervision framework and cross- ...
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In this paper, we present a novel cross-consistency based semi-supervised approach for semantic segmenta- tion. Consistency training has proven to be a ...