Shallow Feature Matters for Weakly Supervised Object Localization
Shallow Feature Matters for Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) aims to localize objects by only utilizing image-level labels. Class activation maps (CAMs) are the commonly used features to achieve WSOL. However, previous CAM-based methods did not take full advantage of the shallow features, despite their importance for WSOL. Because shallow features are easily buried …