SLIC Superpixels Compared to State-of-the-Art Superpixel Methods, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.11, pp.2274-2282, 2012. ,
DOI : 10.1109/TPAMI.2012.120
PatchMatch: A randomized correspondence algorithm for structural image editing, ACM Trans. Graph, vol.28, issue.3, 2009. ,
DOI : 10.1145/2018396.2018421
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.4194
Fast approximate nearest neighbors with automatic algorithm configuration, pp.331-340, 2009. ,
Coherency sensitive hashing, Proc. IEEE ICCV, pp.1607-1614, 2011. ,
DOI : 10.1109/iccv.2011.6126421
TreeCANN - k-d Tree Coherence Approximate Nearest Neighbor Algorithm, Proc. ECCV, pp.602-615, 2012. ,
DOI : 10.1007/978-3-642-33765-9_43
The Generalized PatchMatch Correspondence Algorithm, Proc. ECCV, pp.29-43, 2010. ,
DOI : 10.1007/978-3-642-15558-1_3
Superpixel tracking, Proc. IEEE ICCV, pp.1323-1330, 2011. ,
Temporally Consistent Superpixels, 2013 IEEE International Conference on Computer Vision, pp.385-392, 2013. ,
DOI : 10.1109/ICCV.2013.55
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.4355
Adaptive color transfer with relaxed optimal transport, 2014 IEEE International Conference on Image Processing (ICIP), pp.4852-4856, 2014. ,
DOI : 10.1109/ICIP.2014.7025983
URL : https://hal.archives-ouvertes.fr/hal-01002830
Photo stylistic brush: Robust style transfer via superpixel-based bipartite graph, 2016. ,
Saliency detection using superpixel belief propagation, 2014 IEEE International Conference on Image Processing (ICIP), pp.1135-1139, 2014. ,
DOI : 10.1109/ICIP.2014.7025226
GASP: Geometric Association with Surface Patches, 2014 2nd International Conference on 3D Vision, pp.107-114, 2014. ,
DOI : 10.1109/3DV.2014.113
URL : http://arxiv.org/abs/1411.4098
Eikonalbased vertices growing and iterative seeding for efficient graph-based segmentation, Proc. IEEE ICIP, pp.4368-4372, 2014. ,
DOI : 10.1109/icip.2014.7025886
URL : https://hal.archives-ouvertes.fr/hal-01080017
Superpixel Graph Label Transfer with Learned Distance Metric, Proc. ECCV, pp.632-647, 2014. ,
DOI : 10.1007/978-3-319-10590-1_41
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.644.2769
Superpixel based patch match for differently exposed images with moving objects and camera movements, 2015 IEEE International Conference on Image Processing (ICIP), pp.4516-4520, 2015. ,
DOI : 10.1109/ICIP.2015.7351661
PatchMatch filter: Efficient edge-aware filtering meets randomized search for fast correspondence field estimation, Proc. IEEE CVPR, pp.1854-1861, 2013. ,
DOI : 10.1109/cvpr.2013.242
Multiscale conditional random fields for image labeling, Proc. IEEE CVPR, 2004. ,
Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.2019-2026, 2013. ,
DOI : 10.1109/CVPR.2013.263
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.298.9117
Multi-objective convolutional learning for face labeling, Proc. IEEE CVPR, pp.3451-3459, 2015. ,
Fully convolutional networks for semantic segmentation, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3431-3440, 2015. ,
DOI : 10.1109/CVPR.2015.7298965
Labeled faces in the wild: A database for studying face recognition in unconstrained environments, 2007. ,
Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.886-893, 2005. ,
DOI : 10.1109/CVPR.2005.177
URL : https://hal.archives-ouvertes.fr/inria-00548512
Watersheds in digital spaces: an efficient algorithm based on immersion simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.13, issue.6, pp.583-598, 1991. ,
DOI : 10.1109/34.87344
URL : http://biometrics.cse.msu.edu/PRIPSeminar/Watershed/91VincentWatershed.pdf
Quick Shift and Kernel Methods for Mode Seeking, Proc. ECCV, pp.705-718, 2008. ,
DOI : 10.1007/978-3-540-88693-8_52
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.183.8723
Superpixel segmentation using linear spectral clustering, Proc. IEEE CVPR, pp.1356-1363, 2015. ,
Waterpixels, IEEE Transactions on Image Processing, vol.24, issue.11, pp.3707-3716, 2015. ,
DOI : 10.1109/TIP.2015.2451011
URL : https://hal.archives-ouvertes.fr/hal-01212760
SCALP: Superpixels with Contour Adherence using Linear Path, 2016 23rd International Conference on Pattern Recognition (ICPR), pp.2374-2379, 2016. ,
DOI : 10.1109/ICPR.2016.7899991
URL : https://hal.archives-ouvertes.fr/hal-01349569
GLSC: LSC superpixels at over 130??FPS, Journal of Real-Time Image Processing, vol.15, issue.10, pp.1-12, 2016. ,
DOI : 10.1007/s11554-013-0337-2
Multi-Class Segmentation with Relative Location Prior, International Journal of Computer Vision, vol.30, issue.6, pp.300-316, 2008. ,
DOI : 10.1007/s11263-008-0140-x
URL : http://ai.stanford.edu/~koller/Papers/Gould+al:IJCV08.pdf
Superparsing, Proc. ECCV, pp.352-365, 2010. ,
DOI : 10.1007/s11263-012-0574-z
Layered object detection for multi-class segmentation, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.3113-3120, 2010. ,
DOI : 10.1109/CVPR.2010.5540070
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.171.238
Feedforward semantic segmentation with zoom-out features, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3376-3385, 2015. ,
DOI : 10.1109/CVPR.2015.7298959
URL : http://arxiv.org/abs/1412.0774
Guiding model search using segmentation, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.1417-1423, 2005. ,
DOI : 10.1109/ICCV.2005.112
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.3944
Class segmentation and object localization with superpixel neighborhoods, 2009 IEEE 12th International Conference on Computer Vision, pp.670-677, 2009. ,
DOI : 10.1109/ICCV.2009.5459175
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.4613
Contour Detection and Hierarchical Image Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.5, pp.898-916, 2011. ,
DOI : 10.1109/TPAMI.2010.161
Texture synthesis by non-parametric sampling, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.1033-1038, 1999. ,
DOI : 10.1109/ICCV.1999.790383
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.117.2805
A Non-Local Algorithm for Image Denoising, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.60-65, 2005. ,
DOI : 10.1109/CVPR.2005.38
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.103.9157
Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004. ,
DOI : 10.1023/B:VISI.0000029664.99615.94
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.4931
SURF: Speeded up robust features, Proc. ECCV, pp.404-417, 2006. ,
DOI : 10.1007/11744023_32
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.679.3046
Object Description Based on Spatial Relations between Level-Sets, 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), pp.1-7 ,
DOI : 10.1109/DICTA.2012.6411730
URL : https://hal.archives-ouvertes.fr/hal-00756692
Color Object Recognition based on Spatial Relations between Image Layers, Proceedings of the 10th International Conference on Computer Vision Theory and Applications, pp.427-434, 2015. ,
DOI : 10.5220/0005291304270434
Object Detection with Discriminatively Trained Part-Based Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, pp.1627-1645, 2010. ,
DOI : 10.1109/TPAMI.2009.167
Segmentation-Aware Deformable Part Models, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.168-175, 2014. ,
DOI : 10.1109/CVPR.2014.29
URL : https://hal.archives-ouvertes.fr/hal-01109286
Expanded Parts Model for Human Attribute and Action Recognition in Still Images, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.652-659, 2013. ,
DOI : 10.1109/CVPR.2013.90
URL : https://hal.archives-ouvertes.fr/hal-00816144
Fuzzy spatial relationships for image processing and interpretation: a review, Image and Vision Computing, vol.23, issue.2, pp.89-110, 2005. ,
DOI : 10.1016/j.imavis.2004.06.013
Example-based super-resolution, IEEE Computer Graphics and Applications, vol.22, issue.2, pp.56-65, 2002. ,
DOI : 10.1109/38.988747
Cardiac image superresolution with global correspondence using multi-atlas PatchMatch, Proc. MICCAI, pp.9-16, 2013. ,
DOI : 10.1007/978-3-642-40760-4_2
An Optimized PatchMatch for multi-scale and multi-feature label fusion, NeuroImage, vol.124, pp.770-782, 2016. ,
DOI : 10.1016/j.neuroimage.2015.07.076
URL : https://hal.archives-ouvertes.fr/hal-01198703
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS), IEEE Transactions on Medical Imaging, vol.34, issue.10, pp.1993-2024, 2011. ,
DOI : 10.1109/TMI.2014.2377694
URL : https://hal.archives-ouvertes.fr/hal-00935640
Unsupervised Joint Alignment of Complex Images, 2007 IEEE 11th International Conference on Computer Vision, pp.1-8, 2007. ,
DOI : 10.1109/ICCV.2007.4408858
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.464.8754
Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.11, pp.1222-1239, 2001. ,
DOI : 10.1109/34.969114
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.6806
Conditional random fields: Probabilistic models for segmenting and labeling sequence data, Proc. ICML, pp.282-289, 2001. ,
Multi-atlas Segmentation without Registration: A Supervoxel-Based Approach, Proc. MICCAI, pp.535-542, 2013. ,
DOI : 10.1007/978-3-642-40760-4_67
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3918684/pdf
Morphometric analysis of white matter lesions in MR images: method and validation, IEEE Transactions on Medical Imaging, vol.13, issue.4, pp.716-724, 1994. ,
DOI : 10.1109/42.363096
in telecommunications at ENSEIRB-MATMECA School of Engineers, and the M.Sc. in signal and image processing from the University of Bordeaux, France, in 2014. Since, he is pursuing his Ph.D. at the Laboratoire Bordelais de Recherche en Informatique in the field of image processing. His research areas mainly include computer vision and image processing applications with patch-based and superpixel methods ,
and Doctoral degrees in computer science from the University of Caen Basse-Normandie, France, he was an Assistant Professor in computer science with the School of Engineers of Caen, France. Since 2010, he is an Associate Professor with the Computer Science Department, 2009. ,