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» Shape Discovery from Unlabeled Image Collections
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CVPR
2008
IEEE
14 years 11 months ago
Boosted deformable model for human body alignment
This paper studies image alignment, the problem of learning a shape and appearance model from labeled data and efficiently fitting the model to a non-rigid object with large varia...
Xiaoming Liu 0002, Ting Yu, Thomas Sebastian, Pete...
TOG
2012
279views Communications» more  TOG 2012»
12 years 2 days ago
Sketch-based shape retrieval
We develop a system for 3D object retrieval based on sketched feature lines as input. For objective evaluation, we collect a large number of query sketches from human users that a...
Mathias Eitz, Ronald Richter, Tamy Boubekeur, Kris...
BMCBI
2008
93views more  BMCBI 2008»
13 years 9 months ago
Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throug
Background: The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the in...
Zheng Yin, Xiaobo Zhou, Chris Bakal, Fuhai Li, You...
NIPS
2008
13 years 11 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
ICCV
2003
IEEE
14 years 11 months ago
Tales of Shape and Radiance in Multi-view Stereo
To what extent can three-dimensional shape and radiance be inferred from a collection of images? Can the two be estimated separately while retaining optimality? How should the opt...
Stefano Soatto, Anthony J. Yezzi, Hailin Jin