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Models/SERNet-Former

SERNet-Former

Reported on 12 benchmarks across 3 tasks · 1 paper · 6 SOTA

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

Audio7 results

2D Semantic SegmentationonCamVid
mIoU· 2024-01-28
84.62
SOTA
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
2D Semantic SegmentationonCityscapes val
mIoU· 2024-01-28
87.35
SOTA
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
10-shot image generationonCamVid
Mean IoU· 2024-01-28
84.62
SOTA
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
10-shot image generationonCityscapes val
Validation mIoU· 2024-01-28
87.35
SOTA
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
10-shot image generationonCityscapes test
Mean IoU (class)· 2024-01-28
84.83
best: 86.4 (VLTSeg)
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
10-shot image generationonCityscapes val
mIoU· 2024-01-28
87.35
best: 90.3 (EfficientPS (Cityscapes-fine))
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
10-shot image generationonADE20K
Validation mIoU· 2024-01-28
59.35
best: 63.6 (ViT-P (InternImage-H))
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741

Medical5 results

Semantic SegmentationonCamVid
Mean IoU· 2024-01-28
84.62
SOTA
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
Semantic SegmentationonCityscapes val
Validation mIoU· 2024-01-28
87.35
SOTA
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
Semantic SegmentationonCityscapes test
Mean IoU (class)· 2024-01-28
84.83
best: 86.4 (VLTSeg)
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
Semantic SegmentationonCityscapes val
mIoU· 2024-01-28
87.35
best: 90.3 (EfficientPS (Cityscapes-fine))
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741
Semantic SegmentationonADE20K
Validation mIoU· 2024-01-28
59.35
best: 63.6 (ViT-P (InternImage-H))
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks arXiv:2401.15741