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cs.CV2023
Learning from Noisy Labels with Decoupled Meta Label Purifier
Yuanpeng Tu, Boshen Zhang, Yuxi Li +5
Training deep neural networks(DNN) with noisy labels is challenging since DNN can easily memorize inaccurate labels, leading to poor generalization ability. Recently, the meta-lear…
cs.CV2023
Learning with Noisy labels via Self-supervised Adversarial Noisy Masking
Yuanpeng Tu, Boshen Zhang, Yuxi Li +6
Collecting large-scale datasets is crucial for training deep models, annotating the data, however, inevitably yields noisy labels, which poses challenges to deep learning algorithm…
cs.CV2023
Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban Scenes
Yuanpeng Tu, Yuxi Li, Boshen Zhang +4
Robust autonomous driving requires agents to accurately identify unexpected areas (anomalies) in urban scenes. To this end, some critical issues remain open: how to design advisabl…