Segmentation evaluation database

Scores:

This page shows a of tested algorithms, ordered as they perform on the benchmark.

The scores were obtained either by our own tests or published at major computer vision conferences and journals. If you wish to add your algorithms please e-mail your results and reference to your paper to the address at the bottom of this page.

  • Single object database - Single object test


Algorithm
Score
Remarks
Shai Bagon, Oren Boiman and Michal Irani,
"What is a Good Image Segment?
A Unified Approach to Segment Extraction".
ECCV 2008.
0.870.01 Interactive segmentation
Sharon Alpert, Meirav Galun, Ronen Basri
 and Achi Brandt.
"Image Segmentation by Probabilistic Bottom-Up
Aggregation and Cue integration
".
CVPR 2007
0.86 0.012
Automeatic segmentation
 M. Galun, E. Sharon, R. Basri, and A. Brandt.
"Texture segmentation by multiscale aggregation
 of filter responses and shape elements".
ICCV  2003.
0.83 0.016 Automeatic segmentation
 J. Shi and J. Malik. 
"Normalized cuts and image segmentation".
TPAMI, 2000
0.72 0.018 Automeatic segmentation
Dorin Comaniciu and Peter Meer
"Mean shift: A robust approach toward
feature space analysis
".
TPAMI 2002
0.57 0.023
Automeatic segmentation

  • Two objects database - Single object test


Algorithm
Score
Remarks
Sharon Alpert, Meirav Galun, Ronen Basri
 and Achi Brandt.
"Image Segmentation by Probabilistic Bottom-Up
Aggregation and Cue integration
".
CVPR 2007
 0.68 0.0533
Automeatic segmentation
 M. Galun, E. Sharon, R. Basri, and A. Brandt.
"Texture segmentation by multiscale aggregation
 of filter responses and shape elements".
ICCV  2003.
0.66 0.0655 Automeatic segmentation
 Dorin Comaniciu and Peter Meer
"Mean shift: A robust approach toward
feature space analysis
".
TPAMI 2002
0.61 0.023 Automeatic segmentation
 J. Shi and J. Malik. 
"Normalized cuts and image segmentation".
TPAMI, 2000
0.58 0.0596
Automeatic segmentation



    This page is maintained by Sharon Alpert