In computer vision, significant advances have been made on object detection with the rapid
development of deep convolutional neural networks (CNN). This paper provides a …

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 rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …

While general object detection with deep learning has achieved great success in the past
few years, the performance and efficiency of detecting small objects are far from satisfactory …

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 …

Accurately and timely detecting multiscale small objects that contain tens of pixels from
remote sensing images (RSI) remains challenging. Most of the existing solutions primarily …

Detecting small or tiny objects is always a difficult and challenging issue in computer vision.
In this paper, we provide a latest and comprehensive survey of deep learning-based …

In recent years, object detection has experienced impressive progress. Despite these
improvements, there is still a significant gap in the performance between the detection of …

As autonomous vehicles and autonomous racing rise in popularity, so does the need for
faster and more accurate detectors. While our naked eyes are able to extract contextual …

SSD (Single Shot Multibox Detector) is one of the best object detection algorithms with both
high accuracy and fast speed. However, SSD's feature pyramid detection method makes it …