Rgb D Salient Object Detection On Nlpr
평가 지표
Average MAE
S-Measure
max E-Measure
max F-Measure
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Average MAE | S-Measure | max E-Measure | max F-Measure |
|---|---|---|---|---|
| rethinking-rgb-d-salient-object-detection | 0.030 | 91.2 | 95.3 | 89.7 |
| dformer-rethinking-rgbd-representation | 0.016 | 94.2 | 97.1 | 93.9 |
| bbs-net-rgb-d-salient-object-detection-with-a | 0.023 | 93.0 | 96.1 | 91.8 |
| uncertainty-inspired-rgb-d-saliency-detection | 0.025 | 91.7 | - | - |
| bilateral-attention-network-for-rgb-d-salient | 0.024 | 92.5 | 96.1 | 91.4 |
| cola-conditional-dropout-and-language-driven | 0.021 | 93.5 | 95.7 | 90.9 |
| is-depth-really-necessary-for-salient-object | 0.021 | 92.9 | - | 92.9 |
| siamese-network-for-rgb-d-salient-object | 0.023 | 92.6 | 96.4 | 91.7 |
| visual-saliency-transformer | - | 0.932 | - | - |
| jl-dcf-joint-learning-and-densely-cooperative | 0.022 | 92.5 | 96.2 | 91.6 |
| uncertainty-inspired-rgb-d-saliency-detection | 0.024 | 91.9 | - | - |
| spsn-superpixel-prototype-sampling-network | 0.022 | 92.6 | 96.2 | 91.4 |
| uc-net-uncertainty-inspired-rgb-d-saliency | 0.025 | 92.0 | - | - |
| contrast-prior-and-fluid-pyramid-integration | 0.036 | 88.8 | 93.2 | 86.7 |