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» Video summarization with supervised learning
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CVPR
2012
IEEE
12 years 19 days ago
Stream-based Joint Exploration-Exploitation Active Learning
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
VR
2010
IEEE
151views Virtual Reality» more  VR 2010»
13 years 5 months ago
Virtually augmenting hundreds of real pictures: An approach based on learning, retrieval, and tracking
Tracking is a major issue of virtual and augmented reality applications. Single object tracking on monocular video streams is fairly well understood. However, when it comes to mul...
Julien Pilet, Hideo Saito
EMNLP
2010
13 years 5 months ago
Incorporating Content Structure into Text Analysis Applications
In this paper, we investigate how modeling content structure can benefit text analysis applications such as extractive summarization and sentiment analysis. This follows the lingu...
Christina Sauper, Aria Haghighi, Regina Barzilay
ICCV
2009
IEEE
15 years 11 days ago
Learning Deformable Action Templates from Crowded Videos
In this paper, we present a Deformable Action Template (DAT) model that is learnable from cluttered real-world videos with weak supervisions. In our generative model, an action ...
Benjamin Yao, Song-Chun Zhu
CVPR
2010
IEEE
14 years 3 months ago
Unsupervised Learning of Invariant Features Using Video
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
David Stavens, Sebastian Thrun