Object detection, as of one the most fundamental and challenging problems in computer
vision, has received great attention in recent years. Over the past two decades, we have …

Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …

Dynamic neural network is an emerging research topic in deep learning. Compared to static
models which have fixed computational graphs and parameters at the inference stage …

With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …

The" shared head for classification and localization"(sibling head), firstly denominated in
Fast RCNN, has been leading the fashion of the object detection community in the past five …

Though tremendous strides have been made in uncontrolled face detection, accurate and
efficient face localisation in the wild remains an open challenge. This paper presents a …

Due to object detection's close relationship with video analysis and image understanding, it
has attracted much research attention in recent years. Traditional object detection methods …

Abstract Face Super-Resolution (SR) is a domain-specific superresolution problem. The
facial prior knowledge can be leveraged to better super-resolve face images. We present a …

Face recognition (FR) is one of the most popular and long-standing topics in computer
vision. With the recent development of deep learning techniques and large-scale datasets …

Automatically detecting surface defects from images is an essential capability in
manufacturing applications. Traditional image processing techniques are useful in solving a …