Camouflaged Object Detection on CAMO (M, F_beta, E_phi, S_alpha) benchmark leaderboard · SOTA2 Research

Camouflaged Object Detection on CAMO (M, F_beta, E_phi, S_alpha)

0.092M ScoreSINet

Evaluation Results

Method	Links
SINet2026.02		0.092	0.712	0.804	0.745	—
MGL-R2026.02		0.088	0.738	0.812	0.775	—
BSA-Net2026.02		0.079	0.768	0.851	0.796	—
PreyNet2026.02		0.077	0.763	0.854	0.79	—
BGNet2026.03		0.073	—	0.87	0.812	0.749
FEDER2026.02		0.07	0.775	0.87	0.802	—
RUN2026.02		0.07	0.781	0.868	0.806	—
FSEL2026.02		0.069	0.779	0.881	0.816	—
FEDER2026.02		0.068	0.79	0.881	0.807	—
RUN2026.02		0.068	0.801	0.879	0.813	—
DINet2026.03		0.068	—	0.874	0.821	0.79
FSEL2026.02		0.067	0.792	0.889	0.819	—
FEDER2026.03		0.067	—	0.886	0.822	0.809
RUN2026.02		0.066	0.815	0.905	0.843	—
ZoomNet2026.03		0.066	—	0.892	0.82	0.752
RUN2026.02		0.065	0.82	0.912	0.845	—
EAMNet2026.03		0.064	—	0.89	0.831	0.763
EVP2026.03		0.059	—	0.895	0.846	0.777
CODdiff2026.03		0.054	—	0.911	0.839	0.802
FSPNet2026.03		0.05	—	0.899	0.856	0.799
DCNet2026.03		0.05	—	0.922	0.87	0.831
ESNet2026.03		0.05	—	0.918	0.86	0.846
SDRNet2026.03		0.049	—	0.924	0.872	0.826
SARNet2026.03		0.047	—	0.927	0.868	0.828
IPNet2026.03		0.047	—	0.924	0.864	0.836
VSCode2026.03		0.046	—	0.925	0.873	0.844
RUN2026.02		0.045	0.861	0.934	0.877	—
CamoFormer2026.03		0.043	—	0.93	0.876	0.856
CamoDiff2026.02		0.042	0.853	0.936	0.878	—
RUN2026.02		0.042	0.879	0.952	0.885	—
FSEL2026.03		0.04	—	0.942	0.885	0.857
SENet2026.03		0.039	—	0.932	0.888	0.847
KCNet2026.03		0.039	—	0.934	0.882	0.847
BDCLNet2026.03		0.039	—	0.929	0.881	0.845
UGDNet2026.03		0.038	—	0.942	0.888	0.865
CGCOD2026.03		0.036	—	0.947	0.896	0.864
LGSAN2026.03		0.034	—	0.949	0.896	0.87