Superpixel Algorithms

The below table is intended to be a comprehensive list of superpixel algorithms that have been introduced and used so far. This means that I am doing my best to regularly update this list; however, it is probably impossible to read every paper in every conference, journal or from ArXiv that proposes a new superpixel algorithm or introduced a novel variant of an existing one. Therefore, feel free to point me towards new papers.

This list is supposed to be as comprehensive as possible; however, feel free to point me to papers or implementations in the comments.

For some of the papers, I also provide some reading notes.

Benchmarks

There are some benchmarks considering a subset of the above algorithms — including my own Superpixel Benchmark. These papers are listed below; note that the above table of superpixel algorithms also indicates which algorithms are evaluated in the respective papers:

References

• [] F. Meyer. Color image segmentation. International Conference on Image Processing and its Applications, 1992, pp. 303-306.
• [] D. Comaniciu, P. Meer. Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (5) (2002) 603–619.
• [] X. Ren, J. Malik. Learning a classification model for segmentation. International Conference on Computer Vision, 2003, pp. 10–17.
• [] P. F. Felzenswalb, D. P. Huttenlocher. Efficient graph-based image segmentation. International Journal of Computer Vision 59 (2) (2004) 167–181.
• [] L. Grady, G. Funka-Lea. Multi-label image segmentation for medical applications based on graph-theoretic electrical potentials. ECCV Workshops on Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis, 2004, pp. 230–245.
• [] L. Grady. Random walks for image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 28 (11) (2006) 1768–1783.
• [] A. Vedaldi, S. Soatto. Quick shift and kernel methods for mode seeking. European Conference on Computer Vision, Vol. 5305, 2008, pp. 705–718.
• [] F. Drucker, J. MacCormick. Fast superpixels for video analysis. Workshop on Motion and Video Computing, 2009, pp. 1–8.
• [] A. Levinshtein, A. Stere, K. N. Kutulakos, D. J. Fleet, S. J. Dickinson, K. Siddiqi. TurboPixels: Fast superpixels using geometric flows. IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (12) (2009) 2290–2297.
• [] O. Veksler, Y. Boykov, P. Mehrani. Superpixels and supervoxels in an energy optimization framework. European Conference on Computer Vision, Vol. 6315, 2010, pp. 211–224.
• [] R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, S. Susstrunk. SLIC superpixels. Tech. rep., Ecole Polytechnique Federale de Lausanne (2010).
• [] R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, S. Susstrunk. SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (11) (2012) 2274–2281.
• [] R. Mester, C. Conrad, A. Guevara. Multichannel segmentation using contour relaxation: Fast super-pixels and temporal propagation. Scandinavian Conference Image Analysis, 2011, pp. 250–261.
• [] C. Conrad, M. Mertz, R. Mester, Contour-relaxed superpixels. Energy Minimization Methods. Computer Vision and Pattern Recognition, 2013, pp. 280–293.
• [] M. Y. Lui, O. Tuzel, S. Ramalingam, R. Chellappa. Entropy rate superpixel segmentation. IEEE Conference on Computer Vision and Pattern Recognition, 2011, pp. 2097–2104.
• [] Y. Zhang, R. Hartley, J. Mashford, S. Burn. Superpixels via pseudo-boolean optimization. International Conference on Computer Vision, 2011, pp. 1387–1394.
• [] D. Weikersdorfer, D. Gossow, M. Beetz. Depth-adaptive superpixels. International Conference on Pattern Recognition, 2012, pp. 2087–2090.
• [] M. van den Bergh, X. Boix, G. Roig, B. de Capitani, L. van Gool. SEEDS: Superpixels extracted via energy-driven sampling. European Conference on Computer Vision, Vol. 7578, 2012, pp. 13–26.
• [] D. Tang, H. Fu, X. Cao. Topology preserved regular superpixel. IEEE International Conference on Multimedia and Expo, 2012, pp. 765–768.
• [] H. Fu, X. Cao, D. Tang, Y. Han, D. Xu. Regularity preserved superpixels and supervoxels. IEEE Transactions on Multimedia 16 (4) (2014) 1165–1175.
• [] J. Wang, X. Wang. VCells: Simple and efficient superpixels using edge-weighted centroidal voronoi tessellations. IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (6)(2012) 1241–1247.
• [] H. E. Tasli, C. Cigla, T. Gevers, A. A. Alatan. Super pixel extraction via convexity induced boundary adaptation. IEEE International Conference on Multimedia and Expo, 2013, pp. 1–6.
• [] H. E. Tasli, C. Cigla, A. A. Alatan. Convexity constrained efficient superpixel and supervoxel extraction. Signal Processing: Image Communication 33 (2015) 71–85.
• [] J. Papon, A. Abramov, M. Schoeler, F. Wörgötter. Voxel cloud connectivity segmentation - supervoxels for point clouds. IEEE Conference on Computer Vision and Pattern Recognition, 2013, pp. 2027–2034.
• [] P. Neubert, P. Protzel. Compact watershed and preemptive SLIC: on improving trade-offs of superpixel segmentation algorithms. International Conference on Pattern Recognition, 2014, pp. 996–1001.
• [] P. Buyssens, I. Gardin, S. Ruan. Eikonal based region growing for superpixels generation: Application to semi-supervised real time organ segmentation in CT images. Innovation and Research in BioMedical Engineering 35 (1) (2014) 20–26.
• [] P. Buyssens, M. Toutain, A. Elmoataz, O. Lézoray. Eikonal-based vertices growing and iterative seeding for efficient graph-based segmentation. International Conference on Image Processing, 2014, pp. 4368–4372
• [] W. Benesova, M. Kottman. Fast superpixel segmentation using morphological processing. Conference on Machine Vision and Machine Learning, 2014.
• [] V. Machairas, E. Decencière, T. Walter. Waterpixels: Superpixels based on the watershed transformation. International Conference on Image Processing, 2014, pp. 4343–4347.
• [] V. Machairas, M. Faessel, D. Cardenas-Pena, T. Chabardes, T. Walter, E. Decencière. Waterpixels. Transactions on Image Processing 24 (11) (2015) 3707–3716.
• [] J. Yao, M. Boben, S. Fidler, R. Urtasun. Real-time coarse-to-fine topologically preserving segmentation. IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 2947–2955.
• [] Z. Li, J. Chen. Superpixel segmentation using linear spectral clustering. IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 1356–1363.
• [] J. M. R. A. Humayun, F. Li. The middle child problem: Revisiting parametric min-cut and seeds for object proposals. International Conference on Computer Vision, 2015, pp. 1600–1608.
• [] J. Strassburg, R. Grzeszick, L. Rothacker, G. A. Fink. On the influence of superpixel methods for image parsing. International Conference on Computer Vision Theory and Application, 2015, pp. 518–527.
• [] David Stutz, Alexander Hermans, Bastian Leibe. Superpixels: An Evaluation of the State-of-the-Art. CoRR abs/1612.01601 (2016)
• [] David Stutz. Superpixel Segmentation: An Evaluation. GCPR 2015: 555-562
• [] C. Rohkohl, K. Engel, Efficient image segmentation using pairwise pixel similarities, in: DAGM Annual Pattern Recognition Symposium, 2007, pp. 254–263.
• [] D. Engel, L. Spinello, R. Triebel, R. Siegwart, H. H. B ̈ulthoff, C. Curio, Medial features for superpixel segmentation, in: IAPR International Conference on Machine Vision Applications, 2009, pp. 248–252.
• [] A. Ducournau, S. Rital, A. Bretto, B. Laget, Hypergraph coarsening for image superpixelization, in: International Symposium on I/V Communications and Mobile Network, 2010, pp. 1–4.
• [] G. Zeng, P. Wang, J. Wang, R. Gan, H. Zha, Structure-sensitive superpixels via geodesic distance, in: International Conference on Computer Vision, 2011, pp. 447–454.
• [] F. Perbet, A. Maki, Homogeneous superpixels from random walks, in: Machine Vision and Applications, Conference on, 2011, pp. 26–30.
• [] Y. Du, J. Shen, X. Yu, D. Wang, Superpixels using random walker, in: IEEE Global High Tech Congress on Electronics, 2012, pp. 62–63.
• [] J. Yang, Z. Gan, X. Gui, K. Li, C. Hou, 3-d geometry enhanced superpixels for RGB-D data, in: Pacific-Rim Conference on Multimedia, 2013, pp. 35–46.
• [] J. Zhang, C. Kan, A. G. Schwing, R. Urtasun, Estimating the 3d layout of indoor scenes and its clutter from depth sensors, in: International Conference on Computer Vision, 2013, pp. 1273–1280.
• [] Z. Ren, G. Shakhnarovich, Image segmentation by cascaded region agglomeration, in: IEEE Conference on Computer Vision and Pattern Recognition, 2013, pp. 2011–2018.
• [] K.-S. Kim, D. Zhang, M.-C. Kang, S.-J. Ko, Improved simple linear iterative clustering superpixels, in: International Symposium on Consumer Electronics, 2013, pp. 259–260.
• [] J. Shen, Y. Du, W. Wang, X. Li, Lazy random walks for superpixel segmentation, Transactions on Image Processing 23 (4) (2014) 1451–1462.
• [] P. Morerio, L. Marcenaro, C. S. Regazzoni, A generative superpixel method, in: International Conference on Information Fusion, 2014, pp. 1–7.
• [] P. Siva, A. Wong, Grid seams: A fast superpixel algorithm for real-time applications, in: Computer and Robot Vision, Conference on, 2014, pp. 127–134.
• [] S. R. S. P. Malladi, S. Ram, J. J. Rodriguez, Superpixels using morphology for rock image segmentation, in: IEEE Southwest Symposium on Image Analysis and Interpretation, 2014, pp. 145–148.
• [] O. Freifeld, Y. Li, J. W. Fisher, A fast method for inferring high-quality simply-connected superpixels, in: International Conference on Image Processing, 2015, pp. 2184–2188.
• [] J. Lv, An improved slic superpixels using reciprocal nearest neighbor clustering, International Journal of Signal Processing, Image Processing and Pattern Recognition 8 (5) (2015) 239–248.
• [] Yong-Jin Liu, Cheng-Chi Yu, Minjing Yu, Ying He. Manifold SLIC: A Fast Method to Compute Content-Sensitive Superpixels. CVPR, pages 651-659, 2016.
• [] Alastair Philip Moore, Simon J. D. Prince, Jonathan Warrell, Umar Mohammed, Graham Jones. Scene shape priors for superpixel segmentation. ICCV, pages 771-778, 2009.
• [] Yurui Xie, Linfeng Xu, Zhengning Wang. Automated co-superpixel generation via graph matching. Signal, Image and Video Processing 8(4): 753-763, 2014.
• [] Se-Ho Lee, Won-Dong Jang, Chang-Su Kim. Contour-Constrained Superpixels for Image and Video Processing. CVPR, pages 5863-5871, 2017.
• [] Yinlin Hu, Yunsong Li, Rui Song, Peng Rao, Yangli Wang. Minimum barrier superpixel segmentation. Image and Vision Computing, Volume 70, 2018.
• [] Radhakrishna Achanta, Sabine Süsstrunk. Superpixels and Polygons Using Simple Non-iterative Clustering. CVPR, 2017.
• [] Imanol Luengo, Mark Basham, Andrew P. French. SMURFS: Superpixels from Multi-scale Refinement of Super-regions. BMVC, 2016.
• [] Chun-Rong Huang, Wei-An Wang, Szu-Yu Lin, Yen-Yu Lin. USEQ: Ultra-fast superpixel extraction via quantization. ICPR, 2016.
• [] Rémi Giraud, Vinh-Thong Ta, Nicolas Papadakis. SCALP: Superpixels with Contour Adherence using Linear Path. ICPR, 2016.
• [] Jia-Xin Zhao, Ren Bo, Qibin Hou, Ming-Ming Cheng. FLIC: Fast Linear Iterative Clustering with Active Search. CoRR, 2016.
• [] Liuyun Duan, Florent Lafarge. Image partitioning into convex polygons. CVPR, 2015.
• [] Y. J. Liu, M. Yu, B. J. Li and Y. He. Intrinsic Manifold SLIC: A Simple and Efficient Method for Computing Content-Sensitive Superpixels. PAMI, 2017.
• [] Linfeng Xu, Liaoyuan Zeng, Zhengning Wang. Saliency-based superpixels. Signal, Image and Video Processing, 2014.
• [] Jianbing Shen, Xiaopeng Hao, Zhiyuan Liang, Yu Liu, Wenguan Wang, Ling Shao. Real-Time Superpixel Segmentation by DBSCAN Clustering Algorithm. TIP, 2016.
• [] A. P. Moore, S. J. D. Prince, J. Warrell, U. Mohammed, and G. Jones. Superpixel Lattices. In Proc. Computer Vision and Pattern Recognition, pages 1–8, 2008.
• [] A. Schick, M. Fischer, R. Stiefelhagen, Measuring and evaluating the compactness of superpixels, in: International Conference on Pattern Recognition, 2012, pp. 930–934.
• [] P. Neubert, P. Protzel, Superpixel benchmark and comparison, in: Forum Bildverarbeitung, 2012.
• [] P. Neubert, P. Protzel, Evaluating superpixels in video. Metrics beyond figure-ground segmentation, in: British Machine Vision Conference, 2013.
• [] M. Wang, X. Liu, Y. Gao, X. Ma, N. Q. Soomro. Superpixel segmentation: A benchmark. Sig. Proc.: Image Comm. 56: 28-39, 2017.
• [] Rémi Giraud, Vinh-Thong Ta, Nicolas Papadakis. Robust Shape Regularity Criteria for Superpixel Evaluation. ICIP, 2017.