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.
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Single object database - Single object test
Score |
Remarks |
|
"What is a Good Image Segment? A Unified Approach to Segment Extraction". ECCV 2008. |
, 0.87±0.01 | 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 |
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Two objects database - Single object test
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