目标视觉检测是计算机视觉领域的一个重要问题，在视频监控、自主驾驶、人机交互等方面具有重要的研究意义和应用价值.近年来，深度学习在图像分类研究中取得了突破性进展，也带动着目标视觉检测取得突飞猛进的发展.本文综述了深度学习在目标视觉检测中的应用进展与展望.首先对目标视觉检测的基本流程进行总结，并介绍了目标视觉检测研究常用的公共数据集；然后重点介绍了目前发展迅猛的深度学习方法在目标视觉检测中的最新应用进展；最后讨论了深度学习方法应用于目标视觉检测时存在的困难和挑战，并对今后的发展趋势进行展望. ; Visual object detection is an important topic in computer vision, and has great theoretical and practical merits in applications such as visual surveillance, autonomous driving, and human-machine interaction. In recent years, significant breakthroughs of deep learning methods in image recognition research have arisen much attention of researchers and accordingly led to the rapid development of visual object detection. In this paper, we review the current advances and perspectives on the applications of deep learning in visual object detection. Firstly, we present the basic procedure for visual object detection and introduce some newly emerging and commonly used data sets. Then we detail the applications of deep learning techniques in visual object detection. Finally, we make in-depth discussions about the difficulties and challenges brought by deep learning as applied to visual object detection, and propose some perspectives on future trends.