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LabelMe

LabelMe is a project created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) which provides a dataset of digital images… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2013
Highly Cited
2013
In this paper, we introduce a new domain adaptation (DA) algorithm where the source and target domains are represented by… Expand
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Highly Cited
2011
Highly Cited
2011
We introduce an approach to image retrieval and auto-tagging that leverages the implicit information about object importance… Expand
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Highly Cited
2011
Highly Cited
2011
In this paper we present a scalable dataflow hardware architecture optimized for the computation of general-purpose vision… Expand
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2011
2011
When we look at real-world scenes, attention seems disproportionately attracted by texts. In the present study, we tested this… Expand
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Highly Cited
2011
Highly Cited
2011
We propose a novel method for weakly supervised semantic segmentation. Training images are labeled only by the classes they… Expand
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Review
2010
Review
2010
Central to the development of computer vision systems is the collection and use of annotated images spanning our visual world… Expand
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Highly Cited
2009
Highly Cited
2009
Currently, video analysis algorithms suffer from lack of information regarding the objects present, their interactions, as well… Expand
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Highly Cited
2008
Highly Cited
2008
The Internet contains billions of images, freely available online. Methods for efficiently searching this incredibly rich… Expand
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Highly Cited
2006
Highly Cited
2006
Given a large dataset of images, we seek to automatically determine the visually similar object and scene classes together with… Expand
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Highly Cited
2005
Highly Cited
2005
Abstract We seek to build a large collection of images with ground truth labels to be used for object detection and recognition… Expand
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