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» Learning Hierarchical Models of Scenes, Objects, and Parts
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CVPR
2012
IEEE
13 years 7 days ago
Learning shared body plans
We cast the problem of recognizing related categories as a unified learning and structured prediction problem with shared body plans. When provided with detailed annotations of o...
Ian Endres, Vivek Srikumar, Ming-Wei Chang, Derek ...
ECCV
2008
Springer
15 years 11 months ago
SIFT Flow: Dense Correspondence across Different Scenes
While image registration has been studied in different areas of computer vision, aligning images depicting different scenes remains a challenging problem, closer to recognition tha...
Ce Liu, Jenny Yuen, Antonio B. Torralba, Josef Siv...
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
ECCV
2010
Springer
14 years 7 months ago
Non-local Characterization of Scenery Images: Statistics, 3D Reasoning, and a Generative Model
Abstract. This work focuses on characterizing scenery images. We semantically divide the objects in natural landscape scenes into background and foreground and show that the shapes...
Tamar Avraham, Michael Lindenbaum
CVPR
2011
IEEE
14 years 6 months ago
Sharing Features Between Objects and Their Attributes
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
Sung Ju Hwang, Fei Sha, Kristen Grauman