Achieving accurate crowd counting still faces many challenges due to continuous scale variations. To this end, we present an innovative Context-Aware Pyramid Attention Network for crowd counting which is realized by extracting rich contextual features and dealing with dependencies on space and channels....
论文理解《Body Structure Aware Deep Crowd Counting》 论文《Body Structure Aware Deep Crowd Counting》 IEEE TRANSACTIONS ON IMAGE PROCESSING 创新点:从语义场景分析作为出发点,进行人群计数;包含三个关键因素:行人,头部和他们地上下文结构(context structure);行人的语义结构可以提供更丰富的信息用于行人识别; 解决...
论文理解《Body Structure Aware Deep Crowd Counting》 的人群计数的关键因素;然后将人群计数问题转换为多任务学习问题,使语义场景模型分成三个不同的子任务;最后,将深度卷积神经网络运用到一个统一的模式学习子任务,在一个统一的方案中,解决了特征提取和多任务人群...新方法用于人群计数,方法主要关注于人群计数的语义...
This paper investigates the role of global context for crowd counting. Specifically, a pure transformer is used to extract features with global information from overlapping image patches. Inspired by classification, we add a context token to the input sequence, to facilitate information exchange with ...
Achieving accurate crowd counting still faces many challenges due to continuous scale variations. To this end, we present an innovative Context-Aware Pyram
Extensive experiments on three challenging crowd counting datasets (ShanghaiTech, UCF-QNRF, and NWPU) demonstrate that our model is effective and competitive when compared against SOTA crowd counting models. 展开 关键词: crowd counting DETR transformer ...
Crowd counting in the frequency domain. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, USA, 18–24 June 2022; pp. 19618–19627. [Google Scholar] Liu, W.; Salzmann, M.; Fua, P. Context-aware crowd counting. In Proceedings of the...