Deep learning has recently achieved great breakthroughs in some fields of computer vision. Various new deep learning methods and deep neural network models were proposed， and their performance was constantly updated. This paper makes a survey on the new progresses of applications of deep learning on computer vision since 2016 with emphases on some typical networks and models. We first investigate the mainstream deep neural network models for image classification including standard models and light-weight models. Then， we introduce some main methods and models for different computer vision fields including object detection， image segmentation and image super-resolution. Finally， we summarize deep neural network architecture searching methods.