计算机科学 ›› 2025, Vol. 52 ›› Issue (6A): 240800156-7.doi: 10.11896/jsjkx.240800156
金鹭, 刘敏昆, 张春红, 陈可飞, 罗压琼, 李博
JIN Lu, LIU Mingkun, ZHANG Chunhong, CHEN Kefei, LUO Yaqiong, LI Bo
摘要： 针对行人空间特征未对齐以及因遮挡导致网络无法充分表征行人信息的问题,设计了一种结合空间转换与多尺度特征融合的网络。首先,提出了一种增强行人检索的方法,旨在增强网络对特殊样本的识别能力;其次,提出了一种自约束-注意力空间转换网络,以解决行人图像空间语义信息不一致的问题;然后,从网络中提取不同尺度特征,并根据网络各分支特点分别融入坐标注意力、实例批量归一化;最后,将各支路特征进行融合,以获取高表征能力的融合特征。在多个数据集上的实验表明,所提方法相比现有方法的重识别性能更优。
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