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Collections:
- Name: BoxInst
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x A100 GPUs
Architecture:
- ResNet
- FPN
- CondInst
Paper:
URL: https://arxiv.org/abs/2012.02310
Title: 'BoxInst: High-Performance Instance Segmentation with Box Annotations'
README: configs/boxinst/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v3.0.0rc6/mmdet/models/detectors/boxinst.py#L8
Version: v3.0.0rc6
Models:
- Name: boxinst_r50_fpn_ms-90k_coco
In Collection: BoxInst
Config: configs/boxinst/boxinst_r50_fpn_ms-90k_coco.py
Metadata:
Iterations: 90000
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 39.4
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 30.8
Weights: https://download.openmmlab.com/mmdetection/v3.0/boxinst/boxinst_r50_fpn_ms-90k_coco/boxinst_r50_fpn_ms-90k_coco_20221228_163052-6add751a.pth
- Name: boxinst_r101_fpn_ms-90k_coco
In Collection: BoxInst
Config: configs/boxinst/boxinst_r101_fpn_ms-90k_coco.py
Metadata:
Iterations: 90000
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.8
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 32.7
Weights: https://download.openmmlab.com/mmdetection/v3.0/boxinst/boxinst_r101_fpn_ms-90k_coco/boxinst_r101_fpn_ms-90k_coco_20221229_145106-facf375b.pth
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