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...