目标检测强化上下文模型

Double-atrous convolution structure was used in enhanced context module (ECM) of the enhanced context model to reduce parameters while expanding effective receptive field to enhance context information of shallow layers, and ECM flexibly acted on middle shallow prediction layers with less damage to original SSD, forming enhanced context model net (ECMNet). Using input image with size of 300×300, ECMNet obtained mean average precision of 80.52% on PASCAL VOC2007 test set, and achieved 73.5 frames per second on 1080Ti. The experimental results show that ECMNet can effectively enhance context information and achieves a better trade-off in parameter, speed and accuracy, which is superior to many state-of-the-art object detectors.