3 papers
cs.LG2025
Revisiting Sparsity Constraint Under High-Rank Property in Partial Multi-Label Learning
Chongjie Si, Yidan Cui, Fuchao Yang +2
Partial Multi-Label Learning (PML) extends the multi-label learning paradigm to scenarios where each sample is associated with a candidate label set containing both ground-truth la…
cs.LG2025
Why Can Accurate Models Be Learned from Inaccurate Annotations?
Chongjie Si, Yidan Cui, Fuchao Yang +2
Learning from inaccurate annotations has gained significant attention due to the high cost of precise labeling. However, despite the presence of erroneous labels, models trained on…
cs.CV2024
Tendency-driven Mutual Exclusivity for Weakly Supervised Incremental Semantic Segmentation
Chongjie Si, Xuehui Wang, Xiaokang Yang +1
Weakly Incremental Learning for Semantic Segmentation (WILSS) leverages a pre-trained segmentation model to segment new classes using cost-effective and readily available image-lev…