2 papers
cs.CV2024
MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation
Shenwang Jiang, Jianan Li, Ying Wang +4
Noisy labels, inevitably existing in pseudo segmentation labels generated from weak object-level annotations, severely hampers model optimization for semantic segmentation. Previou…
cs.LG2021
Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data
Shenwang Jiang, Jianan Li, Ying Wang +3
Corrupted labels and class imbalance are commonly encountered in practically collected training data, which easily leads to over-fitting of deep neural networks (DNNs). Existing ap…