Table 2 Results of the quantitative evaluation of different ablation models on three benchmark datasets using the four metrics \(S_{\alpha }\), \(E_{\phi }\), \(F_{\beta }^{\omega }\) and \(M\). “\({ \uparrow \mathord{\left/ {\vphantom { \uparrow \downarrow }} \right. \kern-0pt} \downarrow }\)” indicates that bigger or smaller is better.
From: Camouflaged object detection via context and texture-aware hierarchical interaction
Baseline models | CAMO | COD10K | NC4K | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
\(S_{\alpha } \uparrow\) | \(E_{\phi } \uparrow\) | \(F_{\beta }^{\omega } \uparrow\) | \(M \downarrow\) | \(S_{\alpha } \uparrow\) | \(E_{\phi } \uparrow\) | \(F_{\beta }^{\omega } \uparrow\) | \(M \downarrow\) | \(S_{\alpha } \uparrow\) | \(E_{\phi } \uparrow\) | \(F_{\beta }^{\omega } \uparrow\) | \(M \downarrow\) | |
Basic (M1) | 0.854 | 0.902 | 0.771 | 0.059 | 0.836 | 0.898 | 0.692 | 0.034 | 0.870 | 0.915 | 0.783 | 0.042 |
Basic + MFAM (M2) | 0.863 | 0.914 | 0.806 | 0.053 | 0.855 | 0.920 | 0.751 | 0.027 | 0.881 | 0.929 | 0.821 | 0.035 |
Basic + w/o HMIM (M3) | 0.869 | 0.912 | 0.809 | 0.051 | 0.860 | 0.921 | 0.758 | 0.026 | 0.886 | 0.928 | 0.829 | 0.034 |
Basic + MFAM + w/o HMIM (M4) | 0.878 | 0.930 | 0.835 | 0.045 | 0.867 | 0.928 | 0.780 | 0.024 | 0.889 | 0.936 | 0.842 | 0.032 |
Basic + HMIM (M5) | 0.877 | 0.928 | 0.833 | 0.046 | 0.867 | 0.927 | 0.778 | 0.024 | 0.889 | 0.935 | 0.841 | 0.032 |
Basic + HMIM + MFAM (M6) | 0.882 | 0.931 | 0.842 | 0.044 | 0.869 | 0.930 | 0.785 | 0.023 | 0.890 | 0.935 | 0.844 | 0.032 |