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Models/CFDN

CFDN

Reported on 54 benchmarks across 6 tasks · 1 paper · 36 SOTA

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

Methodology36 results

3DonECSSD
F-measure· 2021-10-13
0.951
best: 0.961 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
3DonECSSD
MAE· 2021-10-13
0.033
best: 0.021 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
3DonECSSD
S-Measure· 2021-10-13
0.932
best: 0.948 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
3DonPASCAL-S
F-measure· 2021-10-13
0.891
best: 0.909 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
3DonPASCAL-S
MAE· 2021-10-13
0.039
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
3DonPASCAL-S
S-Measure· 2021-10-13
0.894
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonECSSD
F-measure· 2021-10-13
0.951
best: 0.961 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonECSSD
MAE· 2021-10-13
0.033
best: 0.021 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonECSSD
S-Measure· 2021-10-13
0.932
best: 0.948 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonPASCAL-S
F-measure· 2021-10-13
0.891
best: 0.909 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonPASCAL-S
MAE· 2021-10-13
0.039
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonPASCAL-S
S-Measure· 2021-10-13
0.894
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononECSSD
F-measure· 2021-10-13
0.951
best: 0.961 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononECSSD
MAE· 2021-10-13
0.033
best: 0.021 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononECSSD
S-Measure· 2021-10-13
0.932
best: 0.948 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononPASCAL-S
F-measure· 2021-10-13
0.891
best: 0.909 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononPASCAL-S
MAE· 2021-10-13
0.039
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononPASCAL-S
S-Measure· 2021-10-13
0.894
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konECSSD
F-measure· 2021-10-13
0.951
best: 0.961 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konECSSD
MAE· 2021-10-13
0.033
best: 0.021 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konECSSD
S-Measure· 2021-10-13
0.932
best: 0.948 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konPASCAL-S
F-measure· 2021-10-13
0.891
best: 0.909 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konPASCAL-S
MAE· 2021-10-13
0.039
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konPASCAL-S
S-Measure· 2021-10-13
0.894
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
3DonDUTS-TE
MAE· 2021-10-13
0.048
best: 0.018 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
3DonDUTS-TE
S-Measure· 2021-10-13
0.871
best: 0.944 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
3DonDUTS-TE
max F-measure· 2021-10-13
0.859
best: 0.943 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonDUTS-TE
MAE· 2021-10-13
0.048
best: 0.018 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonDUTS-TE
S-Measure· 2021-10-13
0.871
best: 0.944 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D ClassificationonDUTS-TE
max F-measure· 2021-10-13
0.859
best: 0.943 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononDUTS-TE
MAE· 2021-10-13
0.048
best: 0.018 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononDUTS-TE
S-Measure· 2021-10-13
0.871
best: 0.944 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
2D Object DetectiononDUTS-TE
max F-measure· 2021-10-13
0.859
best: 0.943 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konDUTS-TE
MAE· 2021-10-13
0.048
best: 0.018 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konDUTS-TE
S-Measure· 2021-10-13
0.871
best: 0.944 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
16konDUTS-TE
max F-measure· 2021-10-13
0.859
best: 0.943 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550

Computer Vision18 results

Object DetectiononECSSD
F-measure· 2021-10-13
0.951
best: 0.961 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
Object DetectiononECSSD
MAE· 2021-10-13
0.033
best: 0.021 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
Object DetectiononECSSD
S-Measure· 2021-10-13
0.932
best: 0.948 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
Object DetectiononPASCAL-S
F-measure· 2021-10-13
0.891
best: 0.909 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
Object DetectiononPASCAL-S
MAE· 2021-10-13
0.039
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
Object DetectiononPASCAL-S
S-Measure· 2021-10-13
0.894
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononECSSD
F-measure· 2021-10-13
0.951
best: 0.961 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononECSSD
MAE· 2021-10-13
0.033
best: 0.021 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononECSSD
S-Measure· 2021-10-13
0.932
best: 0.948 (M3Net-S)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononPASCAL-S
F-measure· 2021-10-13
0.891
best: 0.909 (TRACER-TE7)
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononPASCAL-S
MAE· 2021-10-13
0.039
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononPASCAL-S
S-Measure· 2021-10-13
0.894
SOTA
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
Object DetectiononDUTS-TE
MAE· 2021-10-13
0.048
best: 0.018 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
Object DetectiononDUTS-TE
S-Measure· 2021-10-13
0.871
best: 0.944 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
Object DetectiononDUTS-TE
max F-measure· 2021-10-13
0.859
best: 0.943 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononDUTS-TE
MAE· 2021-10-13
0.048
best: 0.018 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononDUTS-TE
S-Measure· 2021-10-13
0.871
best: 0.944 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550
RGB Salient Object DetectiononDUTS-TE
max F-measure· 2021-10-13
0.859
best: 0.943 (BiRefNet (DUTS, HRSOD, UHRSD))
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss arXiv:2110.06550