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Models/C2FNet-V2

C2FNet-V2

Reported on 7 benchmarks across 7 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology4 results

3DonPCOD_1200
S-Measure· 2022-07-27
0.895
best: 0.922 (CMX)
Camouflaged Object Detection via Context-aware Cross-level Fusion arXiv:2207.13362
2D ClassificationonPCOD_1200
S-Measure· 2022-07-27
0.895
best: 0.922 (CMX)
Camouflaged Object Detection via Context-aware Cross-level Fusion arXiv:2207.13362
2D Object DetectiononPCOD_1200
S-Measure· 2022-07-27
0.895
best: 0.922 (CMX)
Camouflaged Object Detection via Context-aware Cross-level Fusion arXiv:2207.13362
16konPCOD_1200
S-Measure· 2022-07-27
0.895
best: 0.922 (CMX)
Camouflaged Object Detection via Context-aware Cross-level Fusion arXiv:2207.13362

Computer Vision3 results

Object DetectiononPCOD_1200
S-Measure· 2022-07-27
0.895
best: 0.922 (CMX)
Camouflaged Object Detection via Context-aware Cross-level Fusion arXiv:2207.13362
Camouflaged Object SegmentationonPCOD_1200
S-Measure· 2022-07-27
0.895
best: 0.922 (CMX)
Camouflaged Object Detection via Context-aware Cross-level Fusion arXiv:2207.13362
Object SegmentationonPCOD_1200
S-Measure· 2022-07-27
0.895
best: 0.922 (CMX)
Camouflaged Object Detection via Context-aware Cross-level Fusion arXiv:2207.13362