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Collections:
- Name: Deformable Convolutional Networks v2
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- Deformable Convolution
Paper:
URL: https://arxiv.org/abs/1811.11168
Title: "Deformable ConvNets v2: More Deformable, Better Results"
README: configs/dcnv2/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/ops/dcn/deform_conv.py#L15
Version: v2.0.0
Models:
- Name: faster-rcnn_r50_fpn_mdconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks v2
Config: configs/dcn/faster-rcnn_r50-mdconv-c3-c5_fpn_1x_coco.py
Metadata:
Training Memory (GB): 4.1
inference time (ms/im):
- value: 56.82
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.4
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco_20200130-d099253b.pth
- Name: faster-rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco
In Collection: Deformable Convolutional Networks v2
Config: configs/dcn/faster-rcnn_r50-mdconv-group4-c3-c5_fpn_1x_coco.py
Metadata:
Training Memory (GB): 4.2
inference time (ms/im):
- value: 57.47
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco_20200130-01262257.pth
- Name: faster-rcnn_r50_fpn_mdpool_1x_coco
In Collection: Deformable Convolutional Networks v2
Config: configs/dcn/faster-rcnn_r50_fpn_mdpool_1x_coco.py
Metadata:
Training Memory (GB): 5.8
inference time (ms/im):
- value: 60.24
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 38.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_mdpool_1x_coco/faster_rcnn_r50_fpn_mdpool_1x_coco_20200307-c0df27ff.pth
- Name: mask-rcnn_r50_fpn_mdconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks v2
Config: configs/dcn/mask-rcnn_r50-mdconv-c3-c5_fpn_1x_coco.py
Metadata:
Training Memory (GB): 4.5
inference time (ms/im):
- value: 66.23
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.5
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco_20200203-ad97591f.pth
- Name: mask-rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco
In Collection: Deformable Convolutional Networks v2
Config: configs/dcn/mask-rcnn_r50-mdconv-c3-c5_fpn_amp-1x_coco.py
Metadata:
Training Memory (GB): 3.1
Training Techniques:
- SGD with Momentum
- Weight Decay
- Mixed Precision Training
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.0
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.6
Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco_20210520_180434-cf8fefa5.pth