Project-Team Galen
Members
Overall Objectives
Research Program
Application Domains
Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
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Bibliography

Major publications by the team in recent years
  • 1M. Blaschko, C. Lampert.
    Learning to Localize Objects with Structured Output Regression, in: Proceedings of the 10th European Conference on Computer Vision: Part I, ECCV '08, 2008, pp. 2–15.
  • 2B. Glocker, A. Sotiras, N. Komodakis, N. Paragios.
    Deformable Registration: Setting the State of the Art with Discrete Methods, in: Annual Reviews on Biomedical Engineering, 2011, pp. 219-244.
  • 3I. Kokkinos.
    Rapid Deformable Object Detection using Dual-Tree Branch-and-Bound, in: Neural Information Processing Systems (NIPS), Granada, Spain, December 2011.
  • 4I. Kokkinos, A. Yuille.
    Inference and Learning with Hierarchical Shape Models, in: International Journal of Computer Vision, 2011, vol. 93, no 2, pp. 201-225.
  • 5N. Komodakis, N. Paragios, G. Tziritas.
    MRF Energy Minimization and Beyond via Dual Decomposition, in: IEEE Trans. Pattern Anal. Mach. Intell., 2011, vol. 33, no 3, pp. 531-552.
  • 6M. P. Kumar, V. Kolmogorov, P. Torr.
    An analysis of convex relaxations for MAP estimation of discrete MRFs, in: JMLR - Journal of Machine Learning Research, 2009.
    http://hal.inria.fr/hal-00773608
  • 7M. P. Kumar, P. Torr, A. Zisserman.
    OBJCUT: Efficient segmentation using top-down and bottom-up cues, in: PAMI - IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010.
    http://hal.inria.fr/hal-00773609
  • 8C. Lampert, M. Blaschko, T. Hofmann.
    Efficient Subwindow Search: A Branch and Bound Framework for Object Localization, in: IEEE Trans. Pattern Anal. Mach. Intell., December 2009, vol. 31, no 12, pp. 2129–2142.
Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 9P.-Y. Baudin.
    De la segmentation au moyen de graphes d'images de muscles striés squelettiques acquises par RMN, Ecole Centrale Paris, May 2013.
    http://hal.inria.fr/tel-00858584
  • 10N. Honnorat.
    Segmentation et suivi de structures curvilinéaires en imagerie interventionnelle, Ecole Centrale Paris, January 2013.
    http://hal.inria.fr/tel-00801865
  • 11I. Kokkinos.
    Apprentissage et Optimization pour des Representations basées sur la Forme, Université Paris-Est, September 2013, Habilitation à Diriger des Recherches.
    http://hal.inria.fr/tel-00857643
  • 12M. P. Kumar.
    Weakly Supervised Learning for Structured Output Prediction, École normale supérieure de Cachan - ENS Cachan, December 2013, Habilitation à Diriger des Recherches.
    http://hal.inria.fr/tel-00943602

Articles in International Peer-Reviewed Journals

  • 13D. Chittajallu, N. Paragios, I. Kakadiaris.
    An Explicit Shape-constrained MRF-based Contour Evolution Method for 2D Medical Image Segmentation, in: IEEE Journal of Biomedical and Health Informatics, April 2013, pp. 2168-2194. [ DOI : 10.1109/JBHI.2013.2257820 ]
    http://hal.inria.fr/hal-00858880
  • 14S. Kadoury, H. Labelle, N. Paragios.
    Spine Segmentation in Medical Images Using Manifold Embeddings and Higher-Order MRFs, in: IEEE Transactions on Medical Imaging, July 2013, vol. 32, no 7, pp. 1227-1238. [ DOI : 10.1109/TMI.2013.2244903 ]
    http://hal.inria.fr/hal-00856319
  • 15A. Panagopoulos, W. Chaohui, D. Samaras, N. Paragios.
    Simultaneous Cast Shadows, Illumination and Geometry Inference Using Hypergraphs, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, February 2013, vol. 35, no 2, pp. 437-449. [ DOI : 10.1109/TPAMI.2012.110 ]
    http://hal.inria.fr/hal-00855591
  • 16A. Sotiras, C. Davatzikos, N. Paragios.
    Deformable Medical Image Registration: A Survey, in: IEEE Transactions on Medical Imaging, May 2013, vol. 32, no 7, pp. 1153-1190. [ DOI : 10.1109/TMI.2013.2265603 ]
    http://hal.inria.fr/hal-00858737
  • 17O. Teboul, I. Kokkinos, L. Simon, K. Panagiotis, N. Paragios.
    Parsing Facades with Shape Grammars and Reinforcement Learning, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, vol. 35, no 7, pp. 1744-1756. [ DOI : 10.1109/TPAMI.2012.252 ]
    http://hal.inria.fr/hal-00855609
  • 18C. Wang, N. Komodakis, N. Paragios.
    Markov Random Field Modeling, Inference & Learning in Computer Vision & Image Understanding: A Survey, in: Computer Vision and Image Understanding, 2013, vol. 117, no 11, pp. 1610-1627. [ DOI : 10.1016/j.cviu.2013.07.004 ]
    http://hal.inria.fr/hal-00858390

International Conferences with Proceedings

  • 19P.-Y. Baudin, D. Goodman, P. Kumar, N. Azzabou, P. G. Carlier, N. Paragios, M. Pawan Kumar.
    Discriminative Parameter Estimation for Random Walks Segmentation, in: 16th International Conference on Medical Image Computing and Computer Assisted Intervention - MICCAI 2013, Nagoya, Japan, September 2013, 8 p.
    http://hal.inria.fr/hal-00856020
  • 20M. Blaschko, J. Kannala, E. Rahtu.
    Non Maximal Suppression in Cascaded Ranking Models, in: Scandanavian Conference on Image Analysis, Espoo, Finland, April 2013, pp. 408-419. [ DOI : 10.1007/978-3-642-38886-6_39 ]
    http://hal.inria.fr/hal-00815374
  • 21M. Blaschko, W. Zaremba, A. Gretton.
    Taxonomic Prediction with Tree-Structured Covariances, in: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Prague, Czech Republic, June 2013, pp. 304-319. [ DOI : 10.1007/978-3-642-40991-2_20 ]
    http://hal.inria.fr/hal-00839775
  • 22H. Boussaid, I. Kokkinos, N. Paragios.
    Rapid Mode Estimation for 3D Brain MRI Tumor Segmentation, in: Energy Minimization Methods in Computer Vision and Pattern Recognition, Lund, Sweden, 2013.
    http://hal.inria.fr/hal-00856770
  • 23E. Ferrante, N. Paragios.
    Non-rigid 2D-3D Medical Image Registration using Markov Random Fields, in: 16th International Conference on Medical Image Computing and Computer Assisted Intervention - MICCAI 2013, Nagoya, Japan, Springer, 2013, vol. 8151, pp. 163-170.
    http://hal.inria.fr/hal-00855662
  • 24K. Gkirtzou, J.-F. Deux, G. Bassez, A. Sotiras, A. Rahmouni, T. Varacca, N. Paragios, M. Blaschko.
    Sparse classification with MRI based markers for neuromuscular disease categorization, in: 4th International Workhop on Machine Learning in Medical Imaging, Nagoya, Japan, Springer, September 2013.
    http://hal.inria.fr/hal-00845126
  • 25K. Gkirtzou, J. Honorio, D. Samaras, R. Goldstein, M. Blaschko.
    fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics, in: 4th International Workhop on Machine Learning in Medical Imaging, Nagoya, Japan, Springer, September 2013.
    http://hal.inria.fr/hal-00845068
  • 26K. Gkirtzou, J. Honorio, D. Samaras, R. Goldstein, M. Blaschko.
    FMRI Analysis of Cocaine Addiction Using K-Support Sparsity, in: International Symposium on Biomedical Imaging, San Francisco, United States, IEEE, January 2013.
    http://hal.inria.fr/hal-00784386
  • 27I. Kokkinos.
    Shufflets: Shared Mid-level Parts for Fast Multi-Category Detection, in: ICCV - International Conference on Computer Vision, Sydney, Australia, 2013.
    http://hal.inria.fr/hal-00857578
  • 28H. Langet, A. Reshef, C. Riddell, Y. Trousset, A. Tenenhaus, E. Lahalle, G. Fleury, N. Paragios.
    Nonlinear diffusion constraints for reconstructing subsampled rotational angiography data, in: Fully3D 2013, Lake Tahoe, California, United States, June 2013, pp. 38-41.
    http://hal.inria.fr/hal-00933983
  • 29S. Parisot, W. Wells Iii, S. Chemouny, H. Duffau, P. Nikos.
    Uncertainty-driven Efficiently-Sampled Sparse Graphical Models for Concurrent Tumor Segmentation and Atlas Registration, in: ICCV - 14th International Conference on Computer Vision, Sydney, Australia, 2013.
    http://hal.inria.fr/hal-00858696
  • 30E. Trulls, I. Kokkinos, A. Sanfeliu, F. Moreno-Noguer.
    Dense Segmentation-aware Descriptors, in: Computer Vision and Pattern Recognition, Portland, Oregon, United States, 2013.
    http://hal.inria.fr/hal-00856023
  • 31B. Xiang, J.-F. Deux, A. Rahmouni, N. Paragios.
    Joint Model-Pixel Segmentation with Pose-invariant Deformable Graph-Priors, in: 16th International Conference on Medical Image Computing and Computer Assisted Intervention, Nagoya, Japan, September 2013.
    http://hal.inria.fr/hal-00856955
  • 32B. Xiang, N. Komodakis, N. Paragios.
    Pose Invariant Deformable Shape Priors Using L1 Higher Order Sparse Graphs, in: 9th International Symposium on Visual Computing - ISVC 2013, Rethymnon, Greece, July 2013.
    http://hal.inria.fr/hal-00856978
  • 33W. Zaremba, A. Gretton, M. Blaschko.
    B-tests: Low Variance Kernel Two-Sample Tests, in: Neural Information Processing Systems, Lake Tahoe, United States, December 2013.
    http://hal.inria.fr/hal-00842098
  • 34W. Zaremba, M. P. Kumar, A. Gramfort, M. Blaschko.
    Learning from M/EEG data with variable brain activation delays, in: International Conference on Information Processing in Medical Imaging, Asilomar, United States, March 2013.
    http://hal.inria.fr/hal-00803981
  • 35Y. Zeng, W. Chaohui, D. Gu, D. Samaras, N. Paragios.
    A Generic Deformation Model for Dense Non-Rigid Surface Registration: a Higher-Order MRF-based Approach, in: IEEE International Conference on Computer Vision 2013 - ICCV 2013, Sydney, Australia, 2013, 8 p.
    http://hal.inria.fr/hal-00856323

Scientific Books (or Scientific Book chapters)

  • 36K. Daniilidis, P. Maragos, N. Paragios.
    International Journal of Computer Vision Special Issue on Novel Representations, Methods, and Algorithms in Computer Vision, Springer, July 2013, 90 p.
    http://hal.inria.fr/hal-00858678
  • 37C. Wang, Y. Zeng, D. Samaras, N. Paragios.
    Modeling Shapes with Higher-Order Graphs: Methodology and Applications, in: Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective, S. J. Dickinson, Z. Pizlo (editors), 2013, pp. 459-471.
    http://hal.inria.fr/hal-00858417

Books or Proceedings Editing

Internal Reports

  • 39A. Argyriou, S. Clémençon, R. Zhang.
    Learning the Graph of Relations Among Multiple Tasks, October 2013.
    http://hal.inria.fr/hal-00940321
  • 40P.-Y. Baudin, D. Goodman, P. Kumar, N. Azzabou, P. G. Carlier, N. Paragios, M. Pawan Kumar.
    Discriminative Parameter Estimation for Random Walks Segmentation: Technical Report, September 2013.
    http://hal.inria.fr/hal-00830564
  • 41M. Pawan Kumar, H. Turki, D. Preston, D. Koller.
    Parameter Estimation and Energy Minimization for Region-based Semantic Segmentation, August 2013.
    http://hal.inria.fr/hal-00857918

Scientific Popularization

Other Publications


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