作者从detector的overfitting at training/quality mismatch at inference问题入手,提出了基于multi-stage的Cascade R-CNN,该网络结构清晰,效果显著,并且能简单移植到其它detector中,带来2-4%的性能提升 论文: Cascade R-CNN: Delving into High Quality Object Detection 论文地址: https://arxiv.org/abs/1712.00726 代码地…
论文提出Cascade RPN算法来提升RPN模块的性能,该算法重点解决了RPN在迭代时anchor和feature不对齐的问题,论文创新点足,效果也很惊艳,相对于原始的RPN提升13.4%AR 论文:Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution 论文地址:https://arxiv.org/abs/1909.06720 代码地址:https://github.co…