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 …

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

Small object detection is a challenging problem in computer vision. It has been widely
applied in defense military, transportation, industry, etc. To facilitate in-depth understanding …

Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …

Deep learning algorithms are a subset of the machine learning algorithms, which aim at
discovering multiple levels of distributed representations. Recently, numerous deep learning …

Abstract The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object
category classification and detection on hundreds of object categories and millions of …

Convolutional Neural Network (CNN) has demonstrated promising performance in single-
label image classification tasks. However, how CNN best copes with multi-label images still …

Modern deep neural network-based object detection methods typically classify candidate
proposals using their interior features. However, global and local surrounding contexts that …

The long-standing goal of localizing every object in an image remains elusive. Manually
annotating objects is quite expensive despite crowd engineering innovations. Current state …

Convolutional Neural Network (CNN) has demonstrated promising performance in single-
label image classification tasks. However, how CNN best copes with multi-label images still …