Learning a classification model for segmentation, Proceedings Ninth IEEE International Conference on Computer Vision, pp.10-17, 2003. ,
DOI : 10.1109/ICCV.2003.1238308
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.115.3292
Efficient Graph-Based Image Segmentation, International Journal of Computer Vision, vol.59, issue.2, pp.167-181, 2004. ,
DOI : 10.1023/B:VISI.0000022288.19776.77
Quick Shift and Kernel Methods for Mode Seeking, Proc. of European Conference on Computer Vision (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 lattices, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008. ,
DOI : 10.1109/CVPR.2008.4587471
TurboPixels: Fast Superpixels Using Geometric Flows, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.12, pp.31-2290, 2009. ,
DOI : 10.1109/TPAMI.2009.96
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.240
Superpixels and Supervoxels in an Energy Optimization Framework, Proc. of European Conference on Computer Vision (ECCV), pp.211-224, 2010. ,
DOI : 10.1007/978-3-642-15555-0_16
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.381.2083
Entropy rate superpixel segmentation, CVPR 2011, pp.2097-2104, 2011. ,
DOI : 10.1109/CVPR.2011.5995323
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.362.8407
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
SEEDS: Superpixels extracted via energy-driven sampling, Proc. of European Conference on Computer Vision (ECCV), pp.13-26, 2012. ,
Contour-Relaxed Superpixels, Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp.280-293, 2013. ,
DOI : 10.1007/978-3-642-40395-8_21
Eikonal-based vertices growing and iterative seeding for efficient graph-based segmentation, 2014 IEEE International Conference on Image Processing (ICIP), pp.4368-4372, 2014. ,
DOI : 10.1109/ICIP.2014.7025886
URL : https://hal.archives-ouvertes.fr/hal-01080017
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
Superpixel segmentation using linear spectral clustering, Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp.1356-1363, 2015. ,
Real-time coarse-to-fine topologically preserving segmentation, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2947-2955, 2015. ,
DOI : 10.1109/CVPR.2015.7298913
BASS: Boundary-Aware Superpixel Segmentation, 2016 23rd International Conference on Pattern Recognition (ICPR), pp.2824-2829, 2016. ,
DOI : 10.1109/ICPR.2016.7900064
Robust superpixels using color and contour features along linear path HAL preprint https, 2017. ,
DOI : 10.1109/icpr.2016.7899991
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
Superpixels, Occlusion and Stereo, 2011 International Conference on Digital Image Computing: Techniques and Applications ,
DOI : 10.1109/DICTA.2011.22
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
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
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
Superparsing, Proc. of European Conference on Computer Vision (ECCV), pp.352-365, 2010. ,
DOI : 10.1007/s11263-012-0574-z
Superpixel Graph Label Transfer with Learned Distance Metric, Proc. of European Conference on Computer Vision (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
SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches, IEEE Transactions on Image Processing, 2017. ,
DOI : 10.1109/TIP.2017.2708504
URL : https://hal.archives-ouvertes.fr/hal-01432116
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
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
Deep convolutional neural fields for depth estimation from a single image, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.5162-5170, 2015. ,
DOI : 10.1109/CVPR.2015.7299152
URL : http://arxiv.org/abs/1411.6387
Superpixel Convolutional Networks Using Bilateral Inceptions, Proc. of European Conference on Computer Vision (ECCV), pp.597-613, 2016. ,
DOI : 10.1007/978-3-319-46448-0_36
URL : http://arxiv.org/abs/1511.06739
A Video Representation Using Temporal Superpixels, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.2051-2058, 2013. ,
DOI : 10.1109/CVPR.2013.267
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.416.2756
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
Compact Watershed and Preemptive SLIC: On Improving Trade-offs of Superpixel Segmentation Algorithms, 2014 22nd International Conference on Pattern Recognition, pp.996-1001, 2014. ,
DOI : 10.1109/ICPR.2014.181
Measuring and evaluating the compactness of superpixels, Proc. of International Conference on Pattern Recognition (ICPR), pp.930-934, 2012. ,
Superpixel benchmark and comparison, Forum Bildverarbeitung, pp.1-12, 2012. ,
Superpixel segmentation: A benchmark, Signal Processing: Image Communication, vol.56, pp.28-39, 2017. ,
DOI : 10.1016/j.image.2017.04.007
Fast superpixel segmentation using morphological processing, Proc. of the Int. Conf. on Machine Vision and Machine Learning (MVML), 2014. ,
Learning to detect natural image boundaries using local brightness, color, and texture cues, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.5, pp.530-549, 2004. ,
DOI : 10.1109/TPAMI.2004.1273918
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.118.2575
Superpixels: An Evaluation of the State-of-the-Art, Computer Vision and Image Understanding, 2017. ,
DOI : 10.1016/j.cviu.2017.03.007
On the Influence of Superpixel Methods for Image Parsing, Proceedings of the 10th International Conference on Computer Vision Theory and Applications, pp.518-527, 2015. ,
DOI : 10.5220/0005355705180527
Structure-Sensitive Superpixels via Geodesic Distance, International Journal of Computer Vision, vol.22, issue.8, pp.1-21, 2013. ,
DOI : 10.1007/s11263-012-0588-6
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.278.6834
A Simple Algorithm of Superpixel Segmentation with Boundary Constraint, IEEE Transactions on Circuits and Systems for Video Technology, issue.99, 2016. ,
DOI : 10.1109/TCSVT.2016.2539839
An evaluation of the compactness of superpixels, Pattern Recognition Letters, vol.43, pp.71-80, 2014. ,
DOI : 10.1016/j.patrec.2013.09.013
Fish species recognition by shape analysis of images, Pattern Recognition, vol.23, issue.5, pp.539-544, 1990. ,
DOI : 10.1016/0031-3203(90)90074-U
Bulletin de la société vaudoise des sciences naturelles ´ Etude comparative de la distribution florale dans une portion des Alpes et des, Jura, vol.37, pp.547-579, 1901. ,
Robust shape regularity criteria for superpixel evaluation, Proc. of IEEE International Conference on Image Processing (ICIP), 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01510062
Anisotropic Cheeger Sets and Applications, SIAM Journal on Imaging Sciences, vol.2, issue.4, pp.1211-1254, 2009. ,
DOI : 10.1137/08073696X
Measure of circularity for parts of digital boundaries and its fast computation, Pattern Recognition, vol.43, issue.1, pp.37-46, 2010. ,
DOI : 10.1016/j.patcog.2009.06.014
URL : https://hal.archives-ouvertes.fr/hal-00438631
A hierarchical data structure for picture processing, Computer Graphics and Image Processing, vol.4, issue.2, pp.104-119, 1975. ,
DOI : 10.1016/S0146-664X(75)80003-7
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.416-423, 2001. ,
DOI : 10.1109/ICCV.2001.937655
Decomposing a scene into geometric and semantically consistent regions, 2009 IEEE 12th International Conference on Computer Vision, pp.1-8, 2009. ,
DOI : 10.1109/ICCV.2009.5459211
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.159.3865
Parsing clothing in fashion photographs, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.3570-3577, 2012. ,
DOI : 10.1109/CVPR.2012.6248101
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.233.840
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
Superpixel tracking, Proc. of IEEE International Conference on Computer Vision (ICCV), pp.1323-1330, 2011. ,
Motion Coherent Tracking Using Multi-label MRF Optimization, International Journal of Computer Vision, vol.27, issue.10, pp.190-202, 2012. ,
DOI : 10.1007/s11263-011-0512-5
From contours to regions: An empirical evaluation, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.2294-2301, 2009. ,
DOI : 10.1109/CVPR.2009.5206707
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.4065
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 Laboratoire Bordelais de Recherche en Informatique in the field of image processing. His research areas mainly include computer vision and image processing applications with non-local methods and superpixel representation ,
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. ,