Weakly Supervised Object Detection

Weakly Supervised Object Detection (WSOD) is a task in the field of computer vision that aims to train object detectors using only image-level labels. This task enhances the practicality and generalization ability of models by reducing the reliance on large amounts of annotated data, making it suitable for the rapid analysis and processing of large-scale image datasets, and thus has significant application value.