R. Achanta, SLIC superpixels compared to state-ofthe-art superpixel methods, 2012.

R. Achanta, Superpixels and polygons using simple non-iterative clustering, 2017.

C. Barnes, A randomized correspondence algorithm for structural image editing, 2009.

P. Brodatz, Textures : A photographic album for artists and designers, 1966.

P. Buyssens, Eikonal-based region growing for efficient clustering, IVC, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01134406

J. Chen, Linear spectral clustering superpixel, TIP, 2017.

S. He, SuperCNN : A superpixelwise convolutional neural network for salient object detection, IJCV, 2015.

R. Giraud, SuperPatchMatch : An algorithm for robust correspondences using superpixel patches, TIP, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01432116

R. Giraud, Evaluation framework of superpixel methods with a global regularity measure, JEI, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01519635

R. Giraud, Robust superpixels using color and contour features along linear path, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01510063

M. Y. Liu, Entropy rate superpixel segmentation, CVPR, 2011.

Y. Liu, Manifold SLIC : A fast method to compute content-sensitive superpixels, 2016.

D. Martin, A Database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, ICCV, 2001.

M. Reso, Temporally consistent superpixels, ICCV, 2013.

W. Tu, Learning superpixels with segmentationaware affinity loss, 2018.

M. Van-den and . Bergh, SEEDS : Superpixels extracted via energy-driven sampling, 2012.

J. Yan, Object detection by labeling superpixels, 2015.

J. Yao, Real-time coarse-to-fine topologically preserving segmentation, 2015.