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Exploring the Trade-off Between Accuracy and Observational Latency in Action Recognition

International journal of computer vision, 2013-02, Vol.101 (3), p.420-436

2013

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Learning pedestrian dynamics from the real world

2009 IEEE 12th International Conference on Computer Vision, 2009, p.381-388

2009

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IEEE_Xplore

Learning-Based Shadow Recognition and Removal From Monochromatic Natural Images

IEEE transactions on image processing, 2017-12, Vol.26 (12), p.5811-5824

2017

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IEEE_Xplore

Separable Markov Random Field Model and Its Applications in Low Level Vision

IEEE transactions on image processing, 2013-01, Vol.22 (1), p.402-407

2013

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IEEE_Xplore

Recovering intrinsic images from a single image

IEEE transactions on pattern analysis and machine intelligence, 2005-09, Vol.27 (9), p.1459-1472

2005

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IEEE_Xplore

Learning to recognize shadows in monochromatic natural images

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, p.223-230

2010

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IEEE_Xplore

Fundamental Strategies for Solving Low-Level Vision Problems

IPSJ Transactions on Computer Vision and Applications, 2011, Vol.3, pp.95-108

Tappen, Marshall F.

2011

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Context-constrained hallucination for image super-resolution

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, p.231-238

2010

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IEEE_Xplore

Automatic Correction of Saturated Regions in Photographs using Cross-Channel Correlation

Computer graphics forum, 2009-10, Vol.28 (7), p.1861-1869

2009

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Learning Gaussian Conditional Random Fields for Low-Level Vision

2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007, p.1-8

2007

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IEEE_Xplore

Discriminative dictionary learning with spatial priors

2013 IEEE International Conference on Image Processing, 2013, p.166-170

2013

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IEEE_Xplore

Learning optimized MAP estimates in continuously-valued MRF models

2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009, p.477-484

2009

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IEEE_Xplore

Latent Pyramidal Regions for Recognizing Scenes

Computer Vision – ECCV 2012, p.228-241

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Fundamental Strategies for Solving Low-Level Vision Problems

Information and Media Technologies, 2012, Vol.7(1), pp.192-205

Tappen, Marshall F.

2012

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Comparison of graph cuts with belief propagation for stereo, using identical MRF parameters

Proceedings Ninth IEEE International Conference on Computer Vision, 2003, p.900-906 vol.2

2003

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IEEE_Xplore

Learning non-local range Markov Random field for image restoration

CVPR 2011, 2011, p.2745-2752

2011

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IEEE_Xplore

Utilizing Variational Optimization to Learn Markov Random Fields

2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007, p.1-8

Tappen, M.F.

2007

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IEEE_Xplore

A Bayesian Approach to Alignment-Based Image Hallucination

Computer Vision – ECCV 2012, p.236-249

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Recovering shape from a single image of a mirrored surface from curvature constraints

CVPR 2011, 2011, p.2545-2552

Tappen, M. F.

2011

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IEEE_Xplore

Exploring the Trade-off Between Accuracy and Observational Latency in Action Recognition: Human-Computer Interaction: Real-Time Vision Aspects of Natural User Interfaces

International journal of computer vision, 2013, Vol.101 (3), p.420-436

2013

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Measuring and reducing observational latency when recognizing actions

2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011, p.422-429

2011

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IEEE_Xplore

Estimating Intrinsic Component Images using Non-Linear Regression

2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06), 2006, Vol.2, p.1992-1999

2006

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IEEE_Xplore

Optimizing one-shot recognition with micro-set learning

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, p.3027-3034

2010

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IEEE_Xplore

The Logistic Random Field - A convenient graphical model for learning parameters for MRF-based labeling

2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008, p.1-8

2008

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IEEE_Xplore

Playing with Puffball: simple scale-invariant inflation for use in vision and graphics

Proceedings of the ACM Symposium on Applied Perception, 2012, p.47-54

2012

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Exploring the Trade-off Between Accuracy and Observational Latency in Action Recognition

Learning pedestrian dynamics from the real world

Learning-Based Shadow Recognition and Removal From Monochromatic Natural Images

Separable Markov Random Field Model and Its Applications in Low Level Vision

Recovering intrinsic images from a single image

Learning to recognize shadows in monochromatic natural images

Fundamental Strategies for Solving Low-Level Vision Problems

Context-constrained hallucination for image super-resolution

Automatic Correction of Saturated Regions in Photographs using Cross-Channel Correlation

Learning Gaussian Conditional Random Fields for Low-Level Vision

Discriminative dictionary learning with spatial priors

Learning optimized MAP estimates in continuously-valued MRF models

Latent Pyramidal Regions for Recognizing Scenes

Fundamental Strategies for Solving Low-Level Vision Problems

Comparison of graph cuts with belief propagation for stereo, using identical MRF parameters

Learning non-local range Markov Random field for image restoration

Utilizing Variational Optimization to Learn Markov Random Fields

A Bayesian Approach to Alignment-Based Image Hallucination

Recovering shape from a single image of a mirrored surface from curvature constraints

Exploring the Trade-off Between Accuracy and Observational Latency in Action Recognition: Human-Computer Interaction: Real-Time Vision Aspects of Natural User Interfaces

Measuring and reducing observational latency when recognizing actions

Estimating Intrinsic Component Images using Non-Linear Regression

Optimizing one-shot recognition with micro-set learning

The Logistic Random Field - A convenient graphical model for learning parameters for MRF-based labeling

Playing with Puffball: simple scale-invariant inflation for use in vision and graphics

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