Table 3 Comparison of performance...

Table 3

Comparison of performance metrics between proposed and benchmark methods on the NC4K dataset. Only models with less than 50G Multiply-Accumulate Operations (MACs) were considered for computational efficiency. The top-performing method for each metric on each dataset is highlighted in bold, while the second-best method is underscored.

Model	Pub/Year	Input	s_a ↑	$F_{β}^{w} ↑$	M↓	$E_{ϕ}^{m n} ↑$	Para.	MACs
SINet [10]	CVPR’20	352²	0.808	0.723	0.058	0.871	48.95M	19.42G
C2FNet [32]	IJCAF21	352²	0.838	0.762	0.049	0.897	28.41M	13.12G
TINet [48]	AAAF21	352²	0.829	0.734	0.055	0.879	28.56M	8.58G
JSCOD [21]	CVPR’21	352²	0.842	0.771	0.047	0.898	121.63M	25.20G
LSR [24]	CVPR’21	352²	0.840	0.766	0.048	0.895	57.90M	25.21G
PFNet [28]	CVPR’21	416²	0.829	0.745	0.053	0.887	45.64M	26.54G
C2FNet-V2 [1]	TCSVT’22	352²	0.840	0.770	0.048	0.896	44.94M	18.10G
ERRNet [16]	PR’22	352²	0.827	0.737	0.054	0.887	69.76M	20.05G
TPRNet [44]	TVC J’22	352²	0.846	0.768	0.048	0.898	32.95M	12.98G
FAPNet [46]	TIP’22	352²	0.851	0.775	0.047	0.899	29.52M	29.69G
BSANet [47]	AAAI’22	384²	0.841	0.771	0.048	0.897	32.58M	29.70G
SegMaR. [17]	CVPR’22	352²	0.841	0.781	0.046	0.896	56.21M	33.63G
SINetV2 [8]	TPAMI’22	352²	0.847	0.770	0.048	0.903	26.98M	12.28G
DGNet-S [15]	MIR’23	352²	0.845	0.764	0.047	0.902	7.02M	1.20G
DGNet [15]	MIR’23	352²	0.857	0.784	0.042	0.911	19.22M	2.77G
GreenCGD-D3-1000	-	672²	0.815	0.756	0.049	0.884	16.83M	13.70G
GreenCOD-D3-10000	-	672²	0.823	0.766	0.047	0.892	17.62M	15.06G
GreenCGD-D6-1000	-	672²	0.820	0.763	0.047	0.891	17.50M	13.78G
GreenCOD-D6-10000	-	672²	0.827	0.772	0.046	0.893	24.34M	16.22G

Model	Pub/Year	Input	s_a ↑	$F_{β}^{w} ↑$	M↓	$E_{ϕ}^{m n} ↑$	Para.	MACs
SINet [10]	CVPR’20	352²	0.808	0.723	0.058	0.871	48.95M	19.42G
C2FNet [32]	IJCAF21	352²	0.838	0.762	0.049	0.897	28.41M	13.12G
TINet [48]	AAAF21	352²	0.829	0.734	0.055	0.879	28.56M	8.58G
JSCOD [21]	CVPR’21	352²	0.842	0.771	0.047	0.898	121.63M	25.20G
LSR [24]	CVPR’21	352²	0.840	0.766	0.048	0.895	57.90M	25.21G
PFNet [28]	CVPR’21	416²	0.829	0.745	0.053	0.887	45.64M	26.54G
C2FNet-V2 [1]	TCSVT’22	352²	0.840	0.770	0.048	0.896	44.94M	18.10G
ERRNet [16]	PR’22	352²	0.827	0.737	0.054	0.887	69.76M	20.05G
TPRNet [44]	TVC J’22	352²	0.846	0.768	0.048	0.898	32.95M	12.98G
FAPNet [46]	TIP’22	352²	0.851	0.775	0.047	0.899	29.52M	29.69G
BSANet [47]	AAAI’22	384²	0.841	0.771	0.048	0.897	32.58M	29.70G
SegMaR. [17]	CVPR’22	352²	0.841	0.781	0.046	0.896	56.21M	33.63G
SINetV2 [8]	TPAMI’22	352²	0.847	0.770	0.048	0.903	26.98M	12.28G
DGNet-S [15]	MIR’23	352²	0.845	0.764	0.047	0.902	7.02M	1.20G
DGNet [15]	MIR’23	352²	0.857	0.784	0.042	0.911	19.22M	2.77G
GreenCGD-D3-1000	-	672²	0.815	0.756	0.049	0.884	16.83M	13.70G
GreenCOD-D3-10000	-	672²	0.823	0.766	0.047	0.892	17.62M	15.06G
GreenCGD-D6-1000	-	672²	0.820	0.763	0.047	0.891	17.50M	13.78G
GreenCOD-D6-10000	-	672²	0.827	0.772	0.046	0.893	24.34M	16.22G

[ViewLarge]

Sharing Unavailable