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Models/SegFormer-B4

SegFormer-B4

Reported on 6 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Medical3 results

Semantic SegmentationonEventScape
mIoU· 2021-05-31
59.86
best: 64.28 (CMX (B4))
SOTA
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers arXiv:2105.15203
Semantic SegmentationonADE20K
Params (M)· uses extra data· 2021-05-31
64.1
best: 3000 (FD-SwinV2-G)
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers arXiv:2105.15203
Semantic SegmentationonADE20K
Validation mIoU· uses extra data· 2021-05-31
51.1
best: 63.6 (ViT-P (InternImage-H))
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers arXiv:2105.15203

Audio3 results

10-shot image generationonEventScape
mIoU· 2021-05-31
59.86
best: 64.28 (CMX (B4))
SOTA
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers arXiv:2105.15203
10-shot image generationonADE20K
Params (M)· uses extra data· 2021-05-31
64.1
best: 3000 (FD-SwinV2-G)
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers arXiv:2105.15203
10-shot image generationonADE20K
Validation mIoU· uses extra data· 2021-05-31
51.1
best: 63.6 (ViT-P (InternImage-H))
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers arXiv:2105.15203