Abstract:Supervised object detection models require fully annotated data for training the network. However, labeling large datasets is a very time-consuming task, therefore, weakly supervised object detection (WSOD) is a substitute approach to fully supervised learning for the object detection task. Many methods have been proposed for WSOD to date, their performance is still lower than supervised approaches since WSOD is a very challenging task. The major problem with existing WSOD methods is partial object detection a… Show more
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