Add to ORKGResearch in object detection and recognition in cluttered scenes requires large image collections with ground truth labels. The labels should provide information about the object classes present in each image, as well as their shape and locations, and possibly other attributes such as pose. Such data is useful for testing, as well as for supervised learning. This project provides a web-based annotation tool that makes it easy to annotate images, and to instantly sharesuch annotations with the community. This tool, plus an initial set of 10,000 images (3000 of which have been labeled), can be found at http://www.csail.mit.edu/$\sim$brussell/research/LabelMe/intro.htm
Abstract With the advances in distributed computation, machine learning and deep neural networks, we...
Recently, a large visual dataset has emerged from a web-based photo service called Flickr which util...
Advances in machine learning (ML) have made it possible to automatically detect Earth science phenom...
Central to the development of computer vision systems is the collection and use of annotated images ...
This folder contains four Image Annotation Datasets (ESPGame, IAPR-TC12, ImageCLEF 2011, ImagCLEF 20...
Automatic image annotation is the task of automatically assigning some form of semantic label to im...
It is very attractive to exploit weakly-labeled image dataset for multi-label annotation application...
It is very attractive to exploit weakly-labeled image dataset for multi-label annotation application...
Abstract-Image annotation is a promlsmg approach to bridging the semantic gap between low-level feat...
In order to semantically label visual objects in a large amount of images, we propose a new approach...
Image annotation tasks always lack accuracy and efficiency. Although many techniques that have been ...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Image annotation is a promising approach to bridging the semantic gap between low-level features and...
Currently, video analysis algorithms suffer from lack of information regarding the objects present, ...
This thesis focuses on automatic image labelling to semantic categories. It describes the theory of ...
Abstract With the advances in distributed computation, machine learning and deep neural networks, we...
Recently, a large visual dataset has emerged from a web-based photo service called Flickr which util...
Advances in machine learning (ML) have made it possible to automatically detect Earth science phenom...
Central to the development of computer vision systems is the collection and use of annotated images ...
This folder contains four Image Annotation Datasets (ESPGame, IAPR-TC12, ImageCLEF 2011, ImagCLEF 20...
Automatic image annotation is the task of automatically assigning some form of semantic label to im...
It is very attractive to exploit weakly-labeled image dataset for multi-label annotation application...
It is very attractive to exploit weakly-labeled image dataset for multi-label annotation application...
Abstract-Image annotation is a promlsmg approach to bridging the semantic gap between low-level feat...
In order to semantically label visual objects in a large amount of images, we propose a new approach...
Image annotation tasks always lack accuracy and efficiency. Although many techniques that have been ...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Image annotation is a promising approach to bridging the semantic gap between low-level features and...
Currently, video analysis algorithms suffer from lack of information regarding the objects present, ...
This thesis focuses on automatic image labelling to semantic categories. It describes the theory of ...
Abstract With the advances in distributed computation, machine learning and deep neural networks, we...
Recently, a large visual dataset has emerged from a web-based photo service called Flickr which util...
Advances in machine learning (ML) have made it possible to automatically detect Earth science phenom...