Rgb D Salient Object Detection On Sip
Metrics
Average MAE
S-Measure
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Average MAE | S-Measure |
|---|---|---|
| progressively-guided-alternate-refinement | 0.059 | 87.5 |
| visual-saliency-transformer | 0.040 | 90.4 |
| uncertainty-inspired-rgb-d-saliency-detection | 0.045 | 88.3 |
| dformer-rethinking-rgbd-representation | 0.032 | 91.5 |
| uncertainty-inspired-rgb-d-saliency-detection | 0.049 | 87.6 |
| bilateral-attention-network-for-rgb-d-salient | 0.052 | 88.3 |
| spsn-superpixel-prototype-sampling-network | 0.042 | 89.2 |
| uc-net-uncertainty-inspired-rgb-d-saliency | 0.051 | 87.5 |
| contrast-prior-and-fluid-pyramid-integration | 0.064 | 85.0 |
| rethinking-rgb-d-salient-object-detection | 0.063 | 86.0 |
| bts-net-bi-directional-transfer-and-selection | 0.044 | 89.6 |
| densely-deformable-efficient-salient-object | 0.043 | - |
| bbs-net-rgb-d-salient-object-detection-with-a | 0.055 | 87.9 |
| siamese-network-for-rgb-d-salient-object | 0.046 | 89.2 |
| jl-dcf-joint-learning-and-densely-cooperative | 0.051 | 87.9 |
| cola-conditional-dropout-and-language-driven | 0.042 | 89.5 |