| 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 | |