2 citations · 5 across the 5 of their papers we have counts for
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cs.CV2023
Masked Cross-image Encoding for Few-shot Segmentation
Wenbo Xu, Huaxi Huang, Ming Cheng +3
Few-shot segmentation (FSS) is a dense prediction task that aims to infer the pixel-wise labels of unseen classes using only a limited number of annotated images. The key challenge…
cs.LG2023★ 1 cited
Channel-Wise Contrastive Learning for Learning with Noisy Labels
Hui Kang, Sheng Liu, Huaxi Huang +1
In real-world datasets, noisy labels are pervasive. The challenge of learning with noisy labels (LNL) is to train a classifier that discerns the actual classes from given instances…
cs.LG2023★ 2 cited
Unleashing the Potential of Regularization Strategies in Learning with Noisy Labels
Hui Kang, Sheng Liu, Huaxi Huang +4
In recent years, research on learning with noisy labels has focused on devising novel algorithms that can achieve robustness to noisy training labels while generalizing to clean da…