Concealed Object Detection

Benchmark Model Rank Results
camouflaged-object-segmentation-on-camoSINet-V2#8S-Measure: 0.820Weighted F-Measure: 0.743MAE: 0.070
camouflaged-object-segmentation-on-chameleonSINetV2-Res2Net-50#6S-measure: 0.888weighted F-measure: 0.816MAE: 0.030
camouflaged-object-segmentation-on-codSINet*#8S-Measure: 0.771Weighted F-Measure: 0.551MAE: 0.051
camouflaged-object-segmentation-on-nc4kSINetV2-Res2Net-50#6S-measure: 0.847weighted F-measure: 0.770MAE: 0.048
camouflaged-object-segmentation-on-pcod-1200SINet-V2#8S-Measure: 0.882
dichotomous-image-segmentation-on-dis-te1SINetV2#15max F-Measure: 0.644weighted F-measure: 0.558MAE: 0.094
dichotomous-image-segmentation-on-dis-te2SINetV2#19max F-Measure: 0.700weighted F-measure: 0.618MAE: 0.099
dichotomous-image-segmentation-on-dis-te3SINetV2#18max F-Measure: 0.730weighted F-measure: 0.641MAE: 0.096
dichotomous-image-segmentation-on-dis-te4SINetV2#21max F-Measure: 0.699weighted F-measure: 0.616MAE: 0.113
dichotomous-image-segmentation-on-dis-vdSINetV2#21max F-Measure: 0.665weighted F-measure: 0.584MAE: 0.110