Our model ranks first in the challenging SOC benchmark up to now (2019.11.6).

python2.7, pytorch 0.4.0

Modify the pathes of backbone and datasets, then run test_CPD.py

VGG16 backbone: google drive, BaiduYun (code: gb5u)

ResNet50 backbone: google drive, BaiduYun (code: klfd)

VGG16 backbone: google drive

ResNet50 backbone: google drive

Maximum F-measure

MAE

pre-computed maps: google drive

BER

@InProceedings{Wu_2019_CVPR,
author = {Wu, Zhe and Su, Li and Huang, Qingming},
title = {Cascaded Partial Decoder for Fast and Accurate Salient Object Detection},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}