An Up-to-Date List of Superpixel Algorithms

Recently, I started reviewing for different conferences and journals. Based on my previous work, specifically the Superpixel Benchmark, I mostly reviewed papers on superpixel algorithms. For most of these algorithms, and additional related work, I made notes; in this article I want to keep track of the algorithms and benchmarks. The goal is to have an up-to-date list of superpixel algorithms and their implementations.

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.

W[], 1992C/C++Code
EAMS[], 2002MatLab/CCode
NC[], 2003MatLab/CCodeNotes
FH[], 2004C/C++CodeNotes
RW[][], 2004MatLab/CCode
SL[], 2008
QS[], 2008MatLab/CCodeNotes
PF[], 2009JavaCode
TP[], 2009MatLab/CCodeNotes
[], 2009
[], 2009
CIS[], 2010C/C++CodeNotes
SLIC[][], 2010C/C++CodeNotes
[], 2010
CRS[][], 2011C/C++CodeNotes
ERS[], 2011C/C++CodeNotes
PB[], 2011C/C++CodeNotes
[], 2011
[], 2011
DASP[], 2012C/C++Code
SEEDS[], 2012C/C++CodeNotes
TPS[][], 2012MatLab/CCodeNotes
VC[], 2012C/C++Code
[], 2012
CCS[][], 2013C/C++Code
VCCS[], 2013C/C++Code
[], 2013
[], 2013
[], 2013
[], 2013
CW[], 2014C/C++Code
ERGC[][], 2014C/C++Code
MSS[], 2014C/C++
preSLIC[], 2014C/C++Code
WP[][], 2014PythonCode
LRW[], 2014
[], 2014
[], 2014
[], 2014
[], 2014
[], 2014Notes
ETPS[], 2015C/C++Code
LSC[], 2015C/C++Code
POISE[], 2015MatLab/CCode
SEAW[], 2015MatLab/CCode
[], 2015
[], 2015
[], 2015Notes
[], 2016
[], 2016Notes
[], 2016Notes
[], 2016Notes
[], 2016Notes
SCALP[], 2016Notes
[], 2017Notes
[], 2017Notes
[], 2017Notes
[], 2018CodeNotes


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:

[], 2011Evaluates Undersegmentation Error, Boundary Recall and runtime; also evaluates superpixel algorithms as pre-processing task for image segmentation.
[], 2012Proposes Corrected Undersegmentation Error; evaluates Undersegmentation Error, Boundary Recall and Robustness against shift, scale, rotation, shear.Project Page
[], 2013Evaluates superpixel segmentations in video; propose Motion Undersegmentation Error and Motion Discontinuity Error.Project Page
[], 2012Introduces compactness metric (CO); evaluates CO only.
[], 2015Evaluates Undersegmentation Error, Boundary Recall and runtime; includes parameter optimization; evaluates on NYUV2 (in 3D, as well); proposes more efficient and improved implementation of SEEDS.Project Page
[], 2016Evaluates (Corrected) Undersegmentation Error, Boundary Recall, Explained Variation, Achievable Segmentation Accuracy and runtime; enforces connectivity and includes parameter optimization; also considers maximum/minimum and standard deviation of metrics and deviation from the desired number of superpixels; evaluates robustness against geometric transformations and noise; evaluates on 5 datasets.Project Page
[], 2017Introduces regularity metric (RI); evaluates Boundary Recall, - Precision and F1 Measure, Compactness, Undersegmentation Error, Sum-of-Squared Error and Explained Variation and runtime; and provide a code library.Code
[], 2017Introduce regularity metric; evaluates regularity only.Notes


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  • [] 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.
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What is your opinion on this article? Did you find it interesting or useful? Let me know your thoughts in the comments below: