Segda: Maximum separable segment mask with pseudo labels for domain adaptive semantic segmentation

A Khandelwal - Proceedings of the IEEE/CVF International …, 2023 - openaccess.thecvf.com
Abstract Unsupervised Domain Adaptation (UDA) aims to solve the problem of label scarcity
of the target domain by transferring the knowledge from the label rich source domain …
被引用次数：2 相关文章

SegDA: Maximum Separable Segment Mask with Pseudo Labels for Domain Adaptive Semantic Segmentation

A Khandelwal - 2023 IEEE/CVF International Conference on …, 2023 - ieeexplore.ieee.org
Unsupervised Domain Adaptation (UDA) aims to solve the problem of label scarcity of the
target domain by transferring the knowledge from the label rich source domain. Usually, the …

SegDA: Maximum Separable Segment Mask with Pseudo Labels for Domain Adaptive Semantic Segmentation

A Khandelwal - 2023 IEEE/CVF International Conference on …, 2023 - computer.org
Abstract Unsupervised Domain Adaptation (UDA) aims to solve the problem of label scarcity
of the target domain by transferring the knowledge from the label rich source domain …

SegDA: Maximum Separable Segment Mask with Pseudo Labels for Domain Adaptive Semantic Segmentation

A Khandelwal - arXiv e-prints, 2023 - ui.adsabs.harvard.edu
Abstract Unsupervised Domain Adaptation (UDA) aims to solve the problem of label scarcity
of the target domain by transferring the knowledge from the label rich source domain …

SegDA: Maximum Separable Segment Mask with Pseudo Labels for Domain Adaptive Semantic Segmentation

A Khandelwal - arXiv preprint arXiv:2308.05851, 2023 - arxiv.org
Unsupervised Domain Adaptation (UDA) aims to solve the problem of label scarcity of the
target domain by transferring the knowledge from the label rich source domain. Usually, the …