Rgb D Salient Object Detection On Des
Metriken
Average MAE
S-Measure
max E-Measure
max F-Measure
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Average MAE | S-Measure | max E-Measure | max F-Measure |
|---|---|---|---|---|
| cola-conditional-dropout-and-language-driven | 0.018 | 93.5 | 96.3 | 92.5 |
| contrast-prior-and-fluid-pyramid-integration | 0.038 | 87.2 | 92.3 | 84.6 |
| dformer-rethinking-rgbd-representation | 0.013 | 94.8 | 98.0 | 95.6 |
| bbs-net-rgb-d-salient-object-detection-with-a | 0.021 | 93.3 | 96.6 | 92.7 |
| uc-net-uncertainty-inspired-rgb-d-saliency | 0.019 | 93.4 | - | - |
| bilateral-attention-network-for-rgb-d-salient | 0.021 | 93.1 | 97.1 | 92.6 |
| spsn-superpixel-prototype-sampling-network | 0.016 | 93.8 | 97.6 | 94.3 |
| is-depth-really-necessary-for-salient-object | 0.023 | 90.8 | - | 92.8 |
| siamese-network-for-rgb-d-salient-object | 0.021 | 93.6 | 97.5 | 92.9 |
| uncertainty-inspired-rgb-d-saliency-detection | 0.016 | 94.0 | - | - |
| bts-net-bi-directional-transfer-and-selection | 0.018 | 94.3 | 97.9 | 94.0 |
| jl-dcf-joint-learning-and-densely-cooperative | 0.022 | 92.9 | 96.8 | 91.9 |
| uncertainty-inspired-rgb-d-saliency-detection | 0.016 | 93.7 | - | - |