Bibliography
Major publications by the team in recent years
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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.
Doctoral Dissertations and Habilitation Theses
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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
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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
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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)
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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
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38N. Paragios, J. Duncan, N. Ayache (editors)
Biomedical Image Analysis: Methodologies And Applications, Springer, 2013, 590 p.
http://hal.inria.fr/inria-00616178
Internal Reports
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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
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42M. Blaschko.
Machine Learning for Neurological Disorders, in: Centraliens, March 2014, no 632, pp. 30-31.
http://hal.inria.fr/hal-00940262
Other Publications
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43A. Argyriou, L. Baldassarre, C. A. Micchelli, M. Pontil.
On Sparsity Inducing Regularization Methods for Machine Learning, 2013, 12 p, arXiv admin note: text overlap with arXiv:1104.1436.
http://hal.inria.fr/hal-00855984 -
44M. Blaschko.
A Note on k-support Norm Regularized Risk Minimization, March 2013.
http://hal.inria.fr/hal-00804592 -
45S. Maji, E. Rahtu, J. Kannala, M. Blaschko, A. Vedaldi.
Fine-Grained Visual Classification of Aircraft, 2013.
http://hal.inria.fr/hal-00842101