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Collections:
- Name: Empirical Attention
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- Deformable Convolution
- FPN
- RPN
- ResNet
- RoIAlign
- Spatial Attention
Paper:
URL: https://arxiv.org/pdf/1904.05873
Title: 'An Empirical Study of Spatial Attention Mechanisms in Deep Networks'
README: configs/empirical_attention/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/ops/generalized_attention.py#L10
Version: v2.0.0
Models:
- Name: faster_rcnn_r50_fpn_attention_1111_1x_coco
In Collection: Empirical Attention
Config: configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_1x_coco.py
Metadata:
Training Memory (GB): 8.0
inference time (ms/im):
- value: 72.46
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/empirical_attention/faster_rcnn_r50_fpn_attention_1111_1x_coco/faster_rcnn_r50_fpn_attention_1111_1x_coco_20200130-403cccba.pth
- Name: faster_rcnn_r50_fpn_attention_0010_1x_coco
In Collection: Empirical Attention
Config: configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_1x_coco.py
Metadata:
Training Memory (GB): 4.2
inference time (ms/im):
- value: 54.35
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 39.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/empirical_attention/faster_rcnn_r50_fpn_attention_0010_1x_coco/faster_rcnn_r50_fpn_attention_0010_1x_coco_20200130-7cb0c14d.pth
- Name: faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco
In Collection: Empirical Attention
Config: configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py
Metadata:
Training Memory (GB): 8.0
inference time (ms/im):
- value: 78.74
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/empirical_attention/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco_20200130-8b2523a6.pth
- Name: faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco
In Collection: Empirical Attention
Config: configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco.py
Metadata:
Training Memory (GB): 4.2
inference time (ms/im):
- value: 58.48
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/empirical_attention/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco_20200130-1a2e831d.pth
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