Skip to main content

Blog

Learn About Our Meetup

5000+ Members

MEETUPS

LEARN, CONNECT, SHARE

Join our meetup, learn, connect, share, and get to know your Toronto AI community. 

JOB POSTINGS

INDEED POSTINGS

Browse through the latest deep learning, ai, machine learning postings from Indeed for the GTA.

CONTACT

CONNECT WITH US

Are you looking to sponsor space, be a speaker, or volunteer, feel free to give us a shout.

[R] Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks

Abstract – Object detection, the computer vision task dealing with detecting instances of objects of a certain class (e.g., ’car’, ’plane’, etc.) in images, attracted a lot of attention from the community during the last six years. This strong interest can be explained not only by the importance this task has for many applications but also by the phenomenal advances in this area since the arrival of deep convolutional neural networks (DCNNs). This article reviews the recent literature on object detection with deep CNN, in a comprehensive way. This study covers not only the design decisions made in modern deep (CNN) object detectors, but also provides an in-depth perspective on the set of challenges currently faced by the computer vision community, as well as some complementary and new directions on how to overcome them. In its last part it goes on to show how object detection can be extended to other modalities and conducted under different constraints. This survey also reviews in its appendix the public datasets and associated state-of-the-art algorithms.

Page -> https://arxiv.org/abs/1809.03193

PDF -> https://arxiv.org/pdf/1809.03193.pdf

submitted by /u/gnavihs
[link] [comments]