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snnetv2-semantic-segmentation
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Models:
- Name: fpn_poolformer_s12_8xb4-40k_ade20k-512x512
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 36.68
  Config: configs/poolformer/fpn_poolformer_s12_8xb4-40k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 32
    Architecture:
    - PoolFormer-S12
    - FPN
    Training Resources: 8x V100 GPUS
    Memory (GB): 4.17
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s12_8x4_512x512_40k_ade20k/fpn_poolformer_s12_8x4_512x512_40k_ade20k_20220501_115154-b5aa2f49.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s12_8x4_512x512_40k_ade20k/fpn_poolformer_s12_8x4_512x512_40k_ade20k_20220501_115154.log.json
  Paper:
    Title: MetaFormer is Actually What You Need for Vision
    URL: https://arxiv.org/abs/2111.11418
  Code: https://github.com/open-mmlab/mmclassification/blob/v0.23.0/mmcls/models/backbones/poolformer.py#L198
  Framework: PyTorch
- Name: fpn_poolformer_s24_8xb4-40k_ade20k-512x512
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 40.12
  Config: configs/poolformer/fpn_poolformer_s24_8xb4-40k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 32
    Architecture:
    - PoolFormer-S24
    - FPN
    Training Resources: 8x V100 GPUS
    Memory (GB): 5.47
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s24_8x4_512x512_40k_ade20k/fpn_poolformer_s24_8x4_512x512_40k_ade20k_20220503_222049-394a7cf7.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s24_8x4_512x512_40k_ade20k/fpn_poolformer_s24_8x4_512x512_40k_ade20k_20220503_222049.log.json
  Paper:
    Title: MetaFormer is Actually What You Need for Vision
    URL: https://arxiv.org/abs/2111.11418
  Code: https://github.com/open-mmlab/mmclassification/blob/v0.23.0/mmcls/models/backbones/poolformer.py#L198
  Framework: PyTorch
- Name: fpn_poolformer_s36_8xb4-40k_ade20k-512x512
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 41.61
  Config: configs/poolformer/fpn_poolformer_s36_8xb4-40k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 32
    Architecture:
    - PoolFormer-S36
    - FPN
    Training Resources: 8x V100 GPUS
    Memory (GB): 6.77
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s36_8x4_512x512_40k_ade20k/fpn_poolformer_s36_8x4_512x512_40k_ade20k_20220501_151122-b47e607d.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s36_8x4_512x512_40k_ade20k/fpn_poolformer_s36_8x4_512x512_40k_ade20k_20220501_151122.log.json
  Paper:
    Title: MetaFormer is Actually What You Need for Vision
    URL: https://arxiv.org/abs/2111.11418
  Code: https://github.com/open-mmlab/mmclassification/blob/v0.23.0/mmcls/models/backbones/poolformer.py#L198
  Framework: PyTorch
- Name: fpn_poolformer_m36_8xb4-40k_ade20k-512x512
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 41.95
  Config: configs/poolformer/fpn_poolformer_m36_8xb4-40k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 32
    Architecture:
    - PoolFormer-M36
    - FPN
    Training Resources: 8x V100 GPUS
    Memory (GB): 8.59
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_m36_8x4_512x512_40k_ade20k/fpn_poolformer_m36_8x4_512x512_40k_ade20k_20220501_164230-3dc83921.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_m36_8x4_512x512_40k_ade20k/fpn_poolformer_m36_8x4_512x512_40k_ade20k_20220501_164230.log.json
  Paper:
    Title: MetaFormer is Actually What You Need for Vision
    URL: https://arxiv.org/abs/2111.11418
  Code: https://github.com/open-mmlab/mmclassification/blob/v0.23.0/mmcls/models/backbones/poolformer.py#L198
  Framework: PyTorch
- Name: fpn_poolformer_m48_8xb4-40k_ade20k-512x512
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 42.43
  Config: configs/poolformer/fpn_poolformer_m48_8xb4-40k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 32
    Architecture:
    - PoolFormer-M48
    - FPN
    Training Resources: 8x V100 GPUS
    Memory (GB): 10.48
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_m48_8x4_512x512_40k_ade20k/fpn_poolformer_m48_8x4_512x512_40k_ade20k_20220504_003923-64168d3b.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_m48_8x4_512x512_40k_ade20k/fpn_poolformer_m48_8x4_512x512_40k_ade20k_20220504_003923.log.json
  Paper:
    Title: MetaFormer is Actually What You Need for Vision
    URL: https://arxiv.org/abs/2111.11418
  Code: https://github.com/open-mmlab/mmclassification/blob/v0.23.0/mmcls/models/backbones/poolformer.py#L198
  Framework: PyTorch