Efficiently solving convex relaxations for MAP estimation

Efficiently solving convex relaxations for MAP estimation

<p>The problem of obtaining the maximum <em>a posteriori</em> (MAP) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build on the tree reweighted message passing (TRW) framework of (Kolmogorov, 20...

Descrizione completa

Dettagli Bibliografici
Autori principali:	Kumar, MP, Torr, PHS
Natura:	Conference item
Lingua:	English
Pubblicazione:	Association for Computing Machinery 2008

Documenti analoghi

An analysis of convex relaxations for MAP estimation
di: Kumar, MP, et al.
Pubblicazione: (2008)

Analyzing convex relaxations for map estimation
di: Kumar, MP, et al.
Pubblicazione: (2011)

An analysis of convex relaxations for MAP estimation of discrete MRFs
di: Pawan Kumar, M, et al.
Pubblicazione: (2009)

Solving Markov random fields using second order cone programming relaxations
di: Kumar, MP, et al.
Pubblicazione: (2006)

Improved moves for truncated convex models
di: Kumar, MP, et al.
Pubblicazione: (2009)

Solving ptychography with a convex relaxation
di: Roarke Horstmeyer, et al.
Pubblicazione: (2015-01-01)

Efficient relaxations for dense CRFs with sparse higher-order potentials
di: Joy, T, et al.
Pubblicazione: (2019)

P3 and beyond: solving energies with higher order cliques
di: Kohli, P, et al.
Pubblicazione: (2007)

Fast memory-efficient generalized belief propagation
di: Kumar, MP, et al.
Pubblicazione: (2006)

Improved moves for truncated convex models
di: Pawan Kumar, M, et al.
Pubblicazione: (2011)

Efficiently solving dynamic Markov random fields using graph cuts
di: Kohli, P, et al.
Pubblicazione: (2005)

Reduce, reuse and recycle: efficiently solving multi-label MRFs
di: Alahari, K, et al.
Pubblicazione: (2008)

Efficient discriminative learning of parts-based models
di: Kumar, MP, et al.
Pubblicazione: (2010)

OBJCUT: efficient segmentation using top-down and bottom-up cues
di: Kumar, MP, et al.
Pubblicazione: (2009)

Estimations of Covering Functionals of Convex Bodies Based on Relaxation Algorithm
di: Man Yu, et al.
Pubblicazione: (2023-04-01)

Overcoming the convex barrier for simplex input
di: Behl, HS, et al.
Pubblicazione: (2021)

On Convex Relaxations in Nonconvex Optimization
di: T. Westerlund, et al.
Pubblicazione: (2011-04-01)

A convex relaxation for approximate global optimization in simultaneous localization and mapping
di: DuHadway, Charles, et al.
Pubblicazione: (2017)

Distributed non-convex ADMM-based inference in large-scale random fields
di: Miksik, O, et al.
Pubblicazione: (2014)

Scaling the convex barrier with active sets
di: De Palma, A, et al.
Pubblicazione: (2021)

P3 & beyond: move making algorithms for solving higher order functions
di: Kohli, P, et al.
Pubblicazione: (2008)

Bayesian model estimation and selection for epipolar geometry and generic manifold fitting
di: Torr, PHS
Pubblicazione: (2002)

MLESAC: a new robust estimator with application to estimating image geometry
di: Torr, PHS, et al.
Pubblicazione: (2000)

Efficient continuous relaxations for dense CRF
di: Bunel, R, et al.
Pubblicazione: (2016)

An object category specific mrf for segmentation
di: Kumar, MP, et al.
Pubblicazione: (2007)

Obj cut
di: Kumar, MP, et al.
Pubblicazione: (2005)

Learning layered motion segmentations of video
di: Kumar, MP, et al.
Pubblicazione: (2005)

Extending pictorial structures for object recognition
di: Kumar, MP, et al.
Pubblicazione: (2004)

An invariant large margin nearest neighbour classifier
di: Kumar, MP, et al.
Pubblicazione: (2007)

Feature based methods for structure and motion estimation
di: Torr, PHS, et al.
Pubblicazione: (2002)

New convex relaxations for MRF inference with unknown graphs
di: Wang, Z, et al.
Pubblicazione: (2020)

The Non-Tightness of a Convex Relaxation to Rotation Recovery
di: Yuval Alfassi, et al.
Pubblicazione: (2021-11-01)

A convex relaxation approach for power flow problem
di: Saeed D. Manshadi, et al.
Pubblicazione: (2019-01-01)

Polynomial Structure in Semidefinite Relaxations and Non-Convex Formulations
di: Yuan, Chenyang
Pubblicazione: (2023)

The development and comparison of robust methods for estimating the fundamental matrix
di: Torr, PHS, et al.
Pubblicazione: (1997)

PoseField: an efficient mean-field based method for joint estimation of human pose, segmentation, and depth
di: Vineet, V, et al.
Pubblicazione: (2013)

Performance characterization of fundamental matrix estimation under image degradation
di: Torr, PHS, et al.
Pubblicazione: (1997)

Dynamic graph cuts for efficient inference in Markov random fields
di: Kohli, P, et al.
Pubblicazione: (2007)

Solving the convex ordered set problem
Pubblicazione: (2003)

Convexity and boundedness relaxation for fixed point theorems in modular spaces
di: Fatemeh Lael, et al.
Pubblicazione: (2021-04-01)