lps
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code for the paper
lps
code for the paper ``learning to promote saliency detectors"
Environment: python 2.7; pytorch '0.5.0a0+54db14e'; two GTX 1080Ti GPU;
usage
modify the path to prior maps, images, groud truth and then run test.py
pre-trained model
performance and results
This version gives slightly different results from the paper.
Prior maps are the results of other methods which are provided by the authors or obtained by runing their code. For example, results of SRM can be downloaded here. Results of applying our method on SRM can be downloaded from 百度网盘 or google drive
F-measure
v | ECSSD | HKU-IS | PASCALS | DUTS-test | THUR | OMRON |
---|---|---|---|---|---|---|
SRM | .8924 | .8739 | .7961 | .7591 | .7079 | .7223 |
+Ours | .9102 | .9032 | .8054 | .7999 | .7299 | .7338 |
MAE
v | ECSSD | HKU-IS | PASCALS | DUTS-test | THUR | OMRON |
---|---|---|---|---|---|---|
SRM | .0542 | .0459 | .0852 | .0633 | .0769 | .0767 |
+Ours | .0416 | .0330 | .0729 | .0536 | .0735 | .0696 |
I'll add the results on other methods later.