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A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018
Ranking-based-Instance-Selection
(L2ID@CVPR2021, TNNLS2022) Boosting Co-teaching with Compression Regularization for Label Noise
The main features of yingyichen-cyy/nested-co-teaching are: Robust Learning Frameworks, Self-Supervised Pretraining.
Open-source alternatives to yingyichen-cyy/nested-co-teaching include: alfredxiangwu/lightcnn — A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018. alibaba-edu/ranking-based-instance-selection — Ranking-based-Instance-Selection. alinlab/selfpatch. alpha-vl/convmae. antoninbrthn/csidn — Code for the article "Confidence Scores Make Instance-dependent Label-noise Learning Possible", ICML'21. aimagelab/mapet.