Semantic Reinforced Attention Learning for Visual Place Recognition
Guohao Peng,Yufeng Yue,Jun Zhang,Zhenyu Wu,Xiaoyu Tang,Danwei Wang,Guohao Peng,Yufeng Yue,Jun Zhang,Zhenyu Wu,Xiaoyu Tang,Danwei Wang
Large-scale visual place recognition (VPR) is inherently challenging because not all visual cues in the image are beneficial to the task. In order to highlight the task-relevant visual cues in the feature embedding, the existing attention mechanisms are either based on artificial rules or trained in a thorough data-driven manner. To fill the gap between the two types, we propose a novel Semantic R...
