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cs.CV2026
Mitigating Instance Entanglement in Instance-Dependent Partial Label Learning
Rui Zhao, Bin Shi, Kai Sun +1
Partial label learning is a prominent weakly supervised classification task, where each training instance is ambiguously labeled with a set of candidate labels. In real-world scena…
cs.CV2024
Estimating Noisy Class Posterior with Part-level Labels for Noisy Label Learning
Rui Zhao, Bin Shi, Jianfei Ruan +2
In noisy label learning, estimating noisy class posteriors plays a fundamental role for developing consistent classifiers, as it forms the basis for estimating clean class posterio…