Skip to search formSkip to main contentSkip to account menu

Object detection

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2018
Highly Cited
2018
We provide a comprehensive evaluation of salient object detection (SOD) models. Our analysis identifies a serious design bias of… 
Highly Cited
2016
Highly Cited
2016
In recent years, we have seen tremendous progress in the field of object detection. Most of the recent improvements have been… 
Highly Cited
2016
Highly Cited
2016
In Convolutional Neural Network (CNN)-based object detection methods, region proposal becomes a bottleneck when objects exhibit… 
Highly Cited
2015
Highly Cited
2015
We propose a bootstrap learning algorithm for salient object detection in which both weak and strong models are exploited. First… 
Highly Cited
2014
Highly Cited
2014
Current high-quality object detection approaches use the scheme of salience-based object proposal methods followed by post… 
Highly Cited
2013
Highly Cited
2013
We propose a novel approach to both learning and detecting local contour-based representations for mid-level features. Our… 
Highly Cited
2012
Highly Cited
2012
A large number of images with ground truth object bounding boxes are critical for learning object detectors, which is a… 
Highly Cited
2011
Highly Cited
2011
We present a novel computational model to explore the relatedness of objectness and saliency, each of which plays an important… 
Review
2008
Review
2008
Identifying moving objects is a critical task for many computer vision applications; it provides a classification of the pixels… 
Highly Cited
1999
Highly Cited
1999
This paper presents an efficient shape-based object detection method based on Distance Transforms and describes its use for real…