Pedro F. Felzenszwalb

发表

David A. Forsyth, Pascal Fua, Terrance E. Boult, 2013, IEEE Trans. Pattern Anal. Mach. Intell..

Distance Transforms of Sampled Functions

Daniel P. Huttenlocher, Pedro F. Felzenszwalb, D. Huttenlocher, 2012, Theory Comput..

From rigid templates to grammars: object detection with structured models

Ross B. Girshick, Pedro F. Felzenszwalb, Ross Girshick, 2012 .

A Min-Cover Approach for Finding Salient Curves

David A. McAllester, Pedro F. Felzenszwalb, 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

Pictorial Structures for Object Recognition

Daniel P. Huttenlocher, Pedro F. Felzenszwalb, D. Huttenlocher, 2004, International Journal of Computer Vision.

Visibility constraints on features of 3D objects

Ronen Basri, David W. Jacobs, Ross B. Girshick, 2009, CVPR.

Fast Inference with Min-Sum Matrix Product

Julian J. McAuley, Pedro F. Felzenszwalb, Julian McAuley, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Efficient Belief Propagation for Early Vision

Daniel P. Huttenlocher, Pedro F. Felzenszwalb, D. Huttenlocher, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

Learning models for object recognition

Pedro F. Felzenszwalb, 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

Hierarchical Matching of Deformable Shapes

Joshua D. Schwartz, Pedro F. Felzenszwalb, Joshua D. Schwartz, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

Pedro F. Felzenszwalb, 2018, ArXiv.

Object Recognition by Combining Appearance and Geometry

Daniel P. Huttenlocher, David J. Crandall, Pedro F. Felzenszwalb, 2006, Toward Category-Level Object Recognition.

Globally optimal pixel labeling algorithms for tree metrics

Éva Tardos, Gyula Pap, Ramin Zabih, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Diffusion Methods for Classification with Pairwise Relationships pdf

Benar Fux Svaiter, Pedro F. Felzenszwalb, B. Svaiter, 2015, Quarterly of Applied Mathematics.

The Generalized A* Architecture pdf

David A. McAllester, Pedro F. Felzenszwalb, 2007, J. Artif. Intell. Res..

Tiered scene labeling with dynamic programming

Olga Veksler, Pedro F. Felzenszwalb, O. Veksler, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Automatic Discovery and Optimization of Parts for Image Classification pdf

Andrew Zisserman, Andrea Vedaldi, Pedro F. Felzenszwalb, 2015, ICLR.

Multiscale Fields of Patterns

Pedro F. Felzenszwalb, John G. Oberlin, John G. Oberlin, 2014, NIPS.

Digipaper: a versatile color document image representation

Daniel P. Huttenlocher, William Rucklidge, Pedro F. Felzenszwalb, 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

Reconfigurable models for scene recognition

Pedro F. Felzenszwalb, Sobhan Naderi Parizi, John G. Oberlin, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Visual object detection with deformable part models

David A. McAllester, Deva Ramanan, Ross B. Girshick, 2013, CACM.

Scene Grammars, Factor Graphs, and Belief Propagation

Pedro F. Felzenszwalb, Jeroen Chua, Jeroen Chua, 2016, J. ACM.

Efficient Graph-Based Image Segmentation

Daniel P. Huttenlocher, Pedro F. Felzenszwalb, D. Huttenlocher, 2004, International Journal of Computer Vision.

Object Detection with Discriminatively Trained Part Based Models

David A. McAllester, Deva Ramanan, Ross B. Girshick, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Sparselet Models for Efficient Multiclass Object Detection

Trevor Darrell, Mario Fritz, Ross B. Girshick, 2012, ECCV.

A Stochastic Grammar for Natural Shapes

Pedro F. Felzenszwalb, 2013, Shape Perception in Human and Computer Vision.

Computing rank-convolutions with a mask

László Babai, Pedro F. Felzenszwalb, L. Babai, 2009, TALG.

Generalized Sparselet Models for Real-Time Multiclass Object Recognition

Trevor Darrell, Ross B. Girshick, Pedro F. Felzenszwalb, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Discriminative Latent Variable Models for Object Detection

David A. McAllester, Deva Ramanan, Ross B. Girshick, 2010, ICML.

Dynamic Programming and Graph Algorithms in Computer Vision

Ramin Zabih, Pedro F. Felzenszwalb, R. Zabih, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Representation and detection of deformable shapes

Pedro F. Felzenszwalb, 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

A discriminatively trained, multiscale, deformable part model

David A. McAllester, Deva Ramanan, Pedro F. Felzenszwalb, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Efficient Belief Propagation for Early Vision

Daniel P. Huttenlocher, Pedro F. Felzenszwalb, D. Huttenlocher, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

Object detection grammars

Pedro F. Felzenszwalb, 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis

Jon M. Kleinberg, Daniel P. Huttenlocher, Pedro F. Felzenszwalb, 2003, NIPS.

Spectral Image Segmentation with Global Appearance Modeling pdf

Pedro F. Felzenszwalb, Jeova F. S. Rocha Neto, 2020, ArXiv.

Efficient matching of pictorial structures

Daniel P. Huttenlocher, Pedro F. Felzenszwalb, D. Huttenlocher, 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

Cascade object detection with deformable part models

David A. McAllester, Ross B. Girshick, Pedro F. Felzenszwalb, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Representation and detection of shapes in images

Pedro F. Felzenszwalb, 2003 .

Image segmentation using local variation

Daniel P. Huttenlocher, Pedro F. Felzenszwalb, D. Huttenlocher, 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

Object recognition with pictorial structures

Pedro F. Felzenszwalb, 2001 .

Object Detection

Yali Amit, Pedro F. Felzenszwalb, Y. Amit, 2020, Computer Vision, A Reference Guide.

Plan-view trajectory estimation with dense stereo background models

Trevor Darrell, Pedro F. Felzenszwalb, David Demirdjian, 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

Object Detection with Grammar Models

David A. McAllester, Ross B. Girshick, Pedro F. Felzenszwalb, 2011, NIPS.

LSVM-MDPM Release 4 Notes

David A. McAllester, Ross B. Girshick, Pedro F. Felzenszwalb, 2010 .

Spatial priors for part-based recognition using statistical models

Daniel P. Huttenlocher, David J. Crandall, Pedro F. Felzenszwalb, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

Representation and detection of deformable shapes

Pedro F. Felzenszwalb, 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

Efficient belief propagation for early vision

Pedro F. Felzenszwalb, D. Huttenlocher, 2004, CVPR 2004.

Efficiently computing a good segmentation

Pedro F. Felzenszwalb, D. Huttenlocher, 1998 .

Deformable Templates I

Pedro F. Felzenszwalb, 2006 .

Pedro F. Felzenszwalb, Sara Sachs, 2016 .

A System for Real Time 3 D Reconstruction by

Pedro F. Felzenszwalb, Nicholas C. Matsakis, C. Stauffer, 2014 .

Discrete Optimization Algorithms in Computer Vision ∗