Search Results for author:
Found 2 papers, 1 papers with code
SFC: Shared Feature Calibration in Weakly Supervised Semantic Segmentation
Specifically, we leverage the class prototypes that carry positive shared features and propose a Multi-Scaled Distribution-Weighted (MSDW) consistency loss for narrowing the gap between the CAMs generated through classifier weights and class prototypes during training.
Weight-guided class complementing for long-tailed image recognition
In this paper, we propose a Weight-Guided Class Complementing framework to address this issue.
Ranked #11 on
Long-tail Learning
on CIFAR-10-LT (ρ=100)
Cannot find the paper you are looking for? You can
Submit a new open access paper.
