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

  1. The best results are highlighted in bold.