Collections:
  - Name: NAS-FPN
    Metadata:
      Training Data: COCO
      Training Techniques:
        - SGD with Momentum
        - Weight Decay
      Training Resources: 8x V100 GPUs
      Architecture:
        - NAS-FPN
        - ResNet
    Paper:
      URL: https://arxiv.org/abs/1904.07392
      Title: 'NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection'
    README: configs/nas_fpn/README.md
    Code:
      URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/necks/nas_fpn.py#L67
      Version: v2.0.0

Models:
  - Name: retinanet_r50_fpn_crop640_50e_coco
    In Collection: NAS-FPN
    Config: configs/nas_fpn/retinanet_r50_fpn_crop640_50e_coco.py
    Metadata:
      Training Memory (GB): 12.9
      inference time (ms/im):
        - value: 43.67
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
          resolution: (800, 1333)
      Epochs: 50
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 37.9
    Weights: https://download.openmmlab.com/mmdetection/v2.0/nas_fpn/retinanet_r50_fpn_crop640_50e_coco/retinanet_r50_fpn_crop640_50e_coco-9b953d76.pth

  - Name: retinanet_r50_nasfpn_crop640_50e_coco
    In Collection: NAS-FPN
    Config: configs/nas_fpn/retinanet_r50_nasfpn_crop640_50e_coco.py
    Metadata:
      Training Memory (GB): 13.2
      inference time (ms/im):
        - value: 43.48
          hardware: V100
          backend: PyTorch
          batch size: 1
          mode: FP32
          resolution: (800, 1333)
      Epochs: 50
    Results:
      - Task: Object Detection
        Dataset: COCO
        Metrics:
          box AP: 40.5
    Weights: https://download.openmmlab.com/mmdetection/v2.0/nas_fpn/retinanet_r50_nasfpn_crop640_50e_coco/retinanet_r50_nasfpn_crop640_50e_coco-0ad1f644.pth