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» Learning and Inference with Constraints
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CVPR
2011
IEEE
13 years 5 months ago
Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation
From conventional wisdom and empirical studies of annotated data, it has been shown that visual statistics such as object frequencies and segment sizes follow power law distributi...
Alex Shyr, Trevor Darrell, Michael Jordan, Raquel ...
COLING
2010
13 years 5 months ago
Acquisition of Unknown Word Paradigms for Large-Scale Grammars
Unknown words are a major issue for large-scale grammars of natural language. We propose a machine learning based algorithm for acquiring lexical entries for all forms in the para...
Kostadin Cholakov, Gertjan van Noord
IJRR
2011
226views more  IJRR 2011»
13 years 4 months ago
Place-dependent people tracking
Abstract People typically move and act under the constraints of an environment, making human behavior strongly place-dependent. Motion patterns, the places and the rates at which p...
Matthias Luber, Gian Diego Tipaldi, Kai Oliver Arr...
CVPR
2009
IEEE
15 years 5 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese
CVPR
2004
IEEE
15 years 1 days ago
Super-Resolution through Neighbor Embedding
In this paper, we propose a novel method for solving single-image super-resolution problems. Given a low-resolution image as input, we recover its highresolution counterpart using...
Hong Chang, Dit-Yan Yeung, Yimin Xiong