Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks
نویسندگان
چکیده
We propose Dense FixMatch, a simple method for online semi-supervised learning of dense and structured prediction tasks combining pseudo-labeling consistency regularization via strong data augmentation. enable the application FixMatch in problems beyond image classification by adding matching operation on pseudo-labels. This allows us to still use full strength augmentation pipelines, including geometric transformations. evaluate it semantic segmentation Cityscapes Pascal VOC with different percentages labeled ablate design choices hyper-parameters. significantly improves results compared supervised using only data, approaching its performance 1/4 samples.
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ژورنال
عنوان ژورنال: Proceedings of the Northern Lights Deep Learning Workshop
سال: 2023
ISSN: ['2703-6928']
DOI: https://doi.org/10.7557/18.6794