Collections:
- Name: FPN
  License: Apache License 2.0
  Metadata:
    Training Data:
    - Cityscapes
    - ADE20K
  Paper:
    Title: Panoptic Feature Pyramid Networks
    URL: https://arxiv.org/abs/1901.02446
  README: configs/sem_fpn/README.md
  Frameworks:
  - PyTorch
Models:
- Name: fpn_r50_4xb2-80k_cityscapes-512x1024
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: Cityscapes
    Metrics:
      mIoU: 74.52
      mIoU(ms+flip): 76.08
  Config: configs/sem_fpn/fpn_r50_4xb2-80k_cityscapes-512x1024.py
  Metadata:
    Training Data: Cityscapes
    Batch Size: 8
    Architecture:
    - R-50
    - FPN
    Training Resources: 4x V100 GPUS
    Memory (GB): 2.8
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/sem_fpn/fpn_r50_512x1024_80k_cityscapes/fpn_r50_512x1024_80k_cityscapes_20200717_021437-94018a0d.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/sem_fpn/fpn_r50_512x1024_80k_cityscapes/fpn_r50_512x1024_80k_cityscapes-20200717_021437.log.json
  Paper:
    Title: Panoptic Feature Pyramid Networks
    URL: https://arxiv.org/abs/1901.02446
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/fpn_head.py#L12
  Framework: PyTorch
- Name: fpn_r101_4xb2-80k_cityscapes-512x1024
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: Cityscapes
    Metrics:
      mIoU: 75.8
      mIoU(ms+flip): 77.4
  Config: configs/sem_fpn/fpn_r101_4xb2-80k_cityscapes-512x1024.py
  Metadata:
    Training Data: Cityscapes
    Batch Size: 8
    Architecture:
    - R-101
    - FPN
    Training Resources: 4x V100 GPUS
    Memory (GB): 3.9
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/sem_fpn/fpn_r101_512x1024_80k_cityscapes/fpn_r101_512x1024_80k_cityscapes_20200717_012416-c5800d4c.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/sem_fpn/fpn_r101_512x1024_80k_cityscapes/fpn_r101_512x1024_80k_cityscapes-20200717_012416.log.json
  Paper:
    Title: Panoptic Feature Pyramid Networks
    URL: https://arxiv.org/abs/1901.02446
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/fpn_head.py#L12
  Framework: PyTorch
- Name: fpn_r50_4xb4-160k_ade20k-512x512
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 37.49
      mIoU(ms+flip): 39.09
  Config: configs/sem_fpn/fpn_r50_4xb4-160k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 16
    Architecture:
    - R-50
    - FPN
    Training Resources: 4x V100 GPUS
    Memory (GB): 4.9
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/sem_fpn/fpn_r50_512x512_160k_ade20k/fpn_r50_512x512_160k_ade20k_20200718_131734-5b5a6ab9.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/sem_fpn/fpn_r50_512x512_160k_ade20k/fpn_r50_512x512_160k_ade20k-20200718_131734.log.json
  Paper:
    Title: Panoptic Feature Pyramid Networks
    URL: https://arxiv.org/abs/1901.02446
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/fpn_head.py#L12
  Framework: PyTorch
- Name: fpn_r101_4xb4-160k_ade20k-512x512
  In Collection: FPN
  Results:
    Task: Semantic Segmentation
    Dataset: ADE20K
    Metrics:
      mIoU: 39.35
      mIoU(ms+flip): 40.72
  Config: configs/sem_fpn/fpn_r101_4xb4-160k_ade20k-512x512.py
  Metadata:
    Training Data: ADE20K
    Batch Size: 16
    Architecture:
    - R-101
    - FPN
    Training Resources: 4x V100 GPUS
    Memory (GB): 5.9
  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/sem_fpn/fpn_r101_512x512_160k_ade20k/fpn_r101_512x512_160k_ade20k_20200718_131734-306b5004.pth
  Training log: https://download.openmmlab.com/mmsegmentation/v0.5/sem_fpn/fpn_r101_512x512_160k_ade20k/fpn_r101_512x512_160k_ade20k-20200718_131734.log.json
  Paper:
    Title: Panoptic Feature Pyramid Networks
    URL: https://arxiv.org/abs/1901.02446
  Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/fpn_head.py#L12
  Framework: PyTorch