We provide the saliency maps (Fetch Code: iirk) for comparisions, including DUTS-OMRON, DUTS-TE, ECSSD, HKU-IS, PASCAL-S. To obtain the same score with our paper, we recommend the evaluation code provided by Feng Mengyang.
| Backbone | # Params | #FLOPs | Saliency maps | Pre-trained model |
|---|---|---|---|---|
| DPNet-50 | 27.1M | 9.2G | maps (Fetch Code: iirk) | model (Fetch Code: 6unj) |
| DPNet-101 | 44.7M | 12.6G | maps (Fetch Code: izwv) | model (Fetch Code: x8h4) |
| DPNet-152 | 59.1M | 16G | maps (Fetch Code: xsx5) | model (Fetch Code: vh5j) |
We also provid the saliency maps (Fetch Code: ezc8) of SOTA models .
In the paper, we compare DPNet with 12 methods on SOC test set (1200 images). The SOC saliency maps of previous methods is borrowed from SRCN project, including DSS、NLDF、SRM、Amulet、DGRL、BMPM、PiCANet-R、R3Net、C2S-Net、RANet、CPD、AFN、BASNet、PoolNet、SCRN、SIBA、EGNet、F3Net、GCPANet、MINet.
Here, we also share our SOC saliency maps (Fetch code:rnsm) for comparison. To obtain the same score with our paper, we recommend the evaluation code provided by Fan Dengping.
Our work is based on F3Net. We fully thank their open-sourced code.