Double-Line Multi-scale Fusion Pedestrian Saliency Detection

摘要：

　　Pedestrian salient detection aims at identifying person body parts in occluded person images,which is greatly significant in occluded person re-identification.To achieve pedestrian salient detection,we propose a double-line multi-scale fusion(DMF)network,which not only extracts double-line features and retains both high-level and low-level semantic information but also fuses high-level information and low-level information for better complement.CRF is then used to further improve its performance.Finally,our method is used to deal with occluded person images into partial person images to achieve partial person reidentification matching.Experiment results on five benchmark datasets show the superiority of our proposed method,and result on two occluded person re-identification datasets indicate the effectiveness of our proposal on pedestrian salient detection.

关键词： Double-line multi-scale fusion network Pedestrian salient detection Occluded person re-identification

作者: Jiaxuan Zhuo Jianhuang Lai

作者单位: The School of Data and Computer Science,Sun Yat-sen University,Guangzhou 510006,China;The Guangdong The School of Data and Computer Science,Sun Yat-sen University,Guangzhou 510006,China;The School of

会议类型: 国际会议

会议名称: 中国模式识别与计算机视觉大会(PRCV2018)

会议地点: 广州

会议语种:英文

页码: 144-154

在线出版日期: 2018-11-23（万方平台首次上网日期，不代表论文的发表时间）