| Collections: | |
| - Name: CentripetalNet | |
| Metadata: | |
| Training Data: COCO | |
| Training Techniques: | |
| - Adam | |
| Training Resources: 16x V100 GPUs | |
| Architecture: | |
| - Corner Pooling | |
| - Stacked Hourglass Network | |
| Paper: | |
| URL: https://arxiv.org/abs/2003.09119 | |
| Title: 'CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection' | |
| README: configs/centripetalnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.5.0/mmdet/models/detectors/cornernet.py#L9 | |
| Version: v2.5.0 | |
| Models: | |
| - Name: centripetalnet_hourglass104_mstest_16x6_210e_coco | |
| In Collection: CentripetalNet | |
| Config: configs/centripetalnet/centripetalnet_hourglass104_mstest_16x6_210e_coco.py | |
| Metadata: | |
| Batch Size: 96 | |
| Training Memory (GB): 16.7 | |
| inference time (ms/im): | |
| - value: 270.27 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 210 | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 44.8 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/centripetalnet/centripetalnet_hourglass104_mstest_16x6_210e_coco/centripetalnet_hourglass104_mstest_16x6_210e_coco_20200915_204804-3ccc61e5.pth | |