TL;DR本文利用神经网络结构搜索技术设计了自动的编译-解码器架构,Automatic Multi-Scale Network (AMSNet),并使用 Scale Pyramid Pooling Loss 优化,解决了像素级隔离问题和多尺度信息的监督,从而在人群计数方面表现出最优异的性能。
Abstract
Most of the recent advances in crowd counting have evolved from hand-designed density estimation networks, where multi-scale features are leveraged to address scale variation, but at the expense of demanding design efforts. In this work, we automate the design of counting models with <