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Class-Aware Contrastive Semi-Supervised Learning. (arXiv:2203.02261v3 [cs.CV] UPDATED)
cs.CV updates on arXiv.org arxiv.org
Pseudo-label-based semi-supervised learning (SSL) has achieved great success
on raw data utilization. However, its training procedure suffers from
confirmation bias due to the noise contained in self-generated artificial
labels. Moreover, the model's judgment becomes noisier in real-world
applications with extensive out-of-distribution data. To address this issue, we
propose a general method named Class-aware Contrastive Semi-Supervised Learning
(CCSSL), which is a drop-in helper to improve the pseudo-label quality and
enhance the model's robustness in the real-world setting. Rather than treating
real-world …
arxiv semi-supervised semi-supervised learning supervised learning