AI RESEARCH
TeD-Loc: Text Distillation for Weakly Supervised Object Localization
arXiv CS.LG
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ArXi:2501.12632v2 Announce Type: replace-cross Weakly supervised object localization (WSOL) models are trained using only image-level class labels. They can predict both the object class and spatial regions corresponding to the object, without requiring explicit bounding box annotations. Given their reliance on classification objectives, traditional WSOL methods, like class activation mapping, tend to focus on the most discriminative object regions, often missing the full spatial extent.