Object detection in 20 years: A survey
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 …
vision, has received great attention in recent years. Over the past two decades, we have …
Investigations of object detection in images/videos using various deep learning techniques and embedded platforms—A comprehensive review
In recent years there has been remarkable progress in one computer vision application
area: object detection. One of the most challenging and fundamental problems in object …
area: object detection. One of the most challenging and fundamental problems in object …
Deep learning in video multi-object tracking: A survey
Abstract The problem of Multiple Object Tracking (MOT) consists in following the trajectory of
different objects in a sequence, usually a video. In recent years, with the rise of Deep …
different objects in a sequence, usually a video. In recent years, with the rise of Deep …
Understanding of object detection based on CNN family and YOLO
J Du - Journal of Physics: Conference Series, 2018 - iopscience.iop.org
As a key use of image processing, object detection has boomed along with the
unprecedented advancement of Convolutional Neural Network (CNN) and its variants since …
unprecedented advancement of Convolutional Neural Network (CNN) and its variants since …
Region-based convolutional networks for accurate object detection and segmentation
Object detection performance, as measured on the canonical PASCAL VOC Challenge
datasets, plateaued in the final years of the competition. The best-performing methods were …
datasets, plateaued in the final years of the competition. The best-performing methods were …
Understanding deep image representations by inverting them
A Mahendran, A Vedaldi - Proceedings of the IEEE …, 2015 - openaccess.thecvf.com
Image representations, from SIFT and Bag of Visual Words to Convolutional Neural
Networks (CNNs), are a crucial component of almost any image understanding system …
Networks (CNNs), are a crucial component of almost any image understanding system …
Rich feature hierarchies for accurate object detection and semantic segmentation
Object detection performance, as measured on the canonical PASCAL VOC dataset, has
plateaued in the last few years. The best-performing methods are complex ensemble …
plateaued in the last few years. The best-performing methods are complex ensemble …
Visualizing deep convolutional neural networks using natural pre-images
A Mahendran, A Vedaldi - International Journal of Computer Vision, 2016 - Springer
Image representations, from SIFT and bag of visual words to convolutional neural networks
(CNNs) are a crucial component of almost all computer vision systems. However, our …
(CNNs) are a crucial component of almost all computer vision systems. However, our …
Deep neural networks for object detection
Abstract Deep Neural Networks (DNNs) have recently shown outstanding performance on
the task of whole image classification. In this paper we go one step further and address the …
the task of whole image classification. In this paper we go one step further and address the …
Scalable object detection using deep neural networks
Deep convolutional neural networks have recently achieved state-of-the-art performance on
a number of image recognition benchmarks, including the ImageNet Large-Scale Visual …
a number of image recognition benchmarks, including the ImageNet Large-Scale Visual …